Dataproc Serverless release notes

These release notes apply to the core Dataproc service, and include:

  • Announcements of the latest Dataproc image versions installed on the Compute Engine VMs used in Dataproc clusters

  • Announcements of new and updated Dataproc and Dataproc Serverless features, bug fixes, known issues, and deprecated functionality

Release schedule: Typically, new Dataproc releases occur at one- to two-week intervals. Releases are rolled out to Compute Engine regions over a 4-day period, with associated release notes published after the rollout completes.

You can see the latest product updates for all of Google Cloud on the Google Cloud page, browse and filter all release notes in the Google Cloud console, or programmatically access release notes in BigQuery.

To get the latest product updates delivered to you, add the URL of this page to your feed reader, or add the feed URL directly.

Important Announcements

  • The Dataproc v1beta2 APIs are deprecated. Use the Dataproc v1 APIs.
  • CentOS 8 has reached its end of life, and packages can no longer be installed from the CentOS 8 mirrors (see the CentOS website the for more information).. This CentOS deprecation affects Dataproc image versions 2.0-centos8 and 1.5-centos8. Note: Attempts to install packages using yum, for example, during cluster creation, will fail. As a short-term mitigation, you can change the yum repository from http://mirror.centos.org to http://vault.centos.org.

October 25, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.124-debian10, 2.0.124-rocky8, 2.0.124-ubuntu18
  • 2.1.72-debian11, 2.1.72-rocky8, 2.1.72-ubuntu20, 2.1.72-ubuntu20-arm
  • 2.2.38-debian12, 2.2.38-rocky9, 2.2.38-ubuntu22

Dataproc Serverless for Spark: Added common AI/ML Python packages by default to Dataproc Serverless for Spark 1.2 and 2.2 runtimes.

Dataproc Serverless for Spark: Upgraded Cloud Storage connector to 3.0.3 version in the latest 1.2 and 2.2 runtimes.

October 21, 2024

Announcing the General Availability (GA) release of Spark UI for Dataproc Serverless Batches and Interactive sessions which allows you to monitor and debug your serverless Spark workloads. Spark UI is available by default and free of cost for all Dataproc Serverless workloads.

October 18, 2024

October 17, 2024

October 14, 2024

Dataproc Clusters created with image versions 2.0.57+, 2.1.5+, or 2.2+: Secondary workers' control plane operations are made by the Dataproc Service Agent service account (service-<project-number>@dataproc-accounts.iam.gserviceaccount.com). They will no longer use the Google APIs Service Agent service account (<project-number>@cloudservices.gserviceaccount.com).

October 11, 2024

October 08, 2024

October 04, 2024

September 30, 2024

Blocklisted the following Dataproc on Compute Engine subminor image versions:

  • 2.0.120-debian10, 2.0.120-rocky8, 2.0.120-ubuntu18
  • 2.1.68-debian11, 2.1.68-rocky8, 2.1.68-ubuntu20, 2.1.68-ubuntu20-arm
  • 2.2.34-debian12, 2.2.34-rocky9, 2.2.34-ubuntu22

September 23, 2024

Dataproc Serverless for Spark: In runtime versions 1.2 and 2.2, minimized the dynamic memory footprint of the Spark application by setting XX:MaxHeapFreeRatio to 30% and XX:MinHeapFreeRatio to 10%.

Dataproc Serverless for Spark: Added the google-cloud-dlp Python package by default to the Dataproc Serverless for Spark runtimes.

Dataproc Serverless for Spark: Fixed an issue that would cause some batches and sessions to fail to start when using the premium compute tier.

September 21, 2024

Blocklisted the following Dataproc on Compute Engine subminor image versions:

  • 2.0.119-debian10, 2.0.103-rocky8, 2.0.103-ubuntu18
  • 2.1.67-debian11, 2.1.51-rocky8, 2.1.51-ubuntu20, 2.1.51-ubuntu20-arm
  • 2.2.33-debian12, 2.2.17-rocky9, 2.2.17-ubuntu22

September 16, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.118-debian10, 2.0.118-rocky8, 2.0.118-ubuntu18
  • 2.1.66-debian11, 2.1.66-rocky8, 2.1.66-ubuntu20, 2.1.66-ubuntu20-arm
  • 2.2.32-debian12, 2.2.32-rocky9, 2.2.32-ubuntu22

September 13, 2024

Dataproc Serverless for Spark: Fixed a bug that caused some batches and sessions to fail to start when using the premium compute tier.

September 06, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.117-debian10, 2.0.117-rocky8, 2.0.117-ubuntu18
  • 2.1.65-debian11, 2.1.65-rocky8, 2.1.65-ubuntu20, 2.1.65-ubuntu20-arm
  • 2.2.31-debian12, 2.2.31-rocky9, 2.2.31-ubuntu22

Dataproc on Compute Engine: The latest 2.2 image versions now support Hudi 0.15.0.

Dataproc on Compute Engine: The latest 2.2 image versions support Hudi Trino integration natively. If both components are selected when you create a Dataproc cluster, Trino will be configured to support Hudi automatically.

September 04, 2024

Dataproc on Compute Engine: Dataproc image version 2.2 will become the default Dataproc on Compute Engine image version on September 6, 2024.

September 03, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.116-debian10, 2.0.116-rocky8, 2.0.116-ubuntu18
  • 2.1.64-debian11, 2.1.64-rocky8, 2.1.64-ubuntu20, 2.1.64-ubuntu20-arm
  • 2.2.30-debian12, 2.2.30-rocky9, 2.2.30-ubuntu22,

Dataproc on Compute Engine: Apache Spark upgraded to version 3.5.1 in image version 2.2 starting with image version 2.2.30.

August 26, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.115-debian10, 2.0.115-rocky8, 2.0.115-ubuntu18
  • 2.1.63-debian11, 2.1.63-rocky8, 2.1.63-ubuntu20, 2.1.63-ubuntu20-arm
  • 2.2.29-debian12, 2.2.29-rocky9, 2.2.29-ubuntu22

August 22, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.77
  • 1.2.21
  • 2.0.85
  • 2.2.21

Dataproc Serverless for Spark: Subminor version 2.0.85 is the last release of runtime version 2.0, which will no longer be supported and will not receive new releases.

August 19, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.114-debian10, 2.0.114-rocky8, 2.0.114-ubuntu18
  • 2.1.62-debian11, 2.1.62-rocky8, 2.1.62-ubuntu20, 2.1.62-ubuntu20-arm
  • 2.2.28-debian12, 2.2.28-rocky9, 2.2.28-ubuntu22

syslog is now available for Dataproc cluster nodes in Cloud Logging. See Dataproc logs for cluster and job log information.

August 15, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.76
  • 1.2.20
  • 2.0.84
  • 2.2.20

August 12, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.75
  • 1.2.19
  • 2.0.83
  • 2.2.19

July 31, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.74
  • 1.2.18
  • 2.0.82
  • 2.2.18

Dataproc Serverless for Spark: Upgraded Spark BigQuery connector to version 0.36.4 in the latest 1.2 and 2.2 Dataproc Serverless for Spark runtime versions.

July 26, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.73
  • 1.2.17
  • 2.0.81
  • 2.2.17

July 25, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.113-debian10, 2.0.113-rocky8, 2.0.113-ubuntu18
  • 2.1.61-debian11, 2.1.61-rocky8, 2.1.61-ubuntu20, 2.1.61-ubuntu20-arm
  • 2.2.27-debian12, 2.2.27-rocky9, 2.2.27-ubuntu22

Enabled user sync by default for clusters using Ranger.

Replaced Spark external packages with connector folder on Dataproc 2.2 clusters.

Fixed a bug that caused intermittent delays and failures in clusters with 3 HDFS.

July 22, 2024

Hyperdisks for Dataproc clusters are now created with default throughput and IOPS. When this behavior becomes configurable, it will be announced in a future release note.

Added support for N4 and C4 machine types for Dataproc image versions 2.1 and above. The following default configurations are now applied to clusters created with N4 or C4 machine types:

  • bootdisktype = "hyperdisk-balanced"
  • nictype = "gvnic"

When a Cluster, Job, AutoscalingPolicy, or WorkflowTemplate API resource does not exist and the requestor does not have access to the project, a 403 error code is now issued instead of a 404 error code.

July 19, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.72
  • 1.2.16
  • 2.0.80
  • 2.2.16

Note: Dataproc Serverless for Spark runtime versions 1.1.71, 1.2.15, 2.0.79, and 2.2.15 were not released.

July 18, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.112-debian10, 2.0.112-rocky8, 2.0.112-ubuntu18
  • 2.1.60-debian11, 2.1.60-rocky8, 2.1.60-ubuntu20, 2.1.60-ubuntu20-arm
  • 2.2.26-debian12, 2.2.26-rocky9, 2.2.26-ubuntu22

July 17, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.70
  • 1.2.14
  • 2.0.78
  • 2.2.14

July 12, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.111-debian10, 2.0.112-rocky8, 2.0.112-ubuntu18
  • 2.1.59-debian11, 2.1.60-rocky8, 2.1.60-ubuntu20, 2.1.60-ubuntu20-arm
  • 2.2.25-debian12, 2.2.26-rocky9, 2.2.26-ubuntu22

July 11, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.69
  • 1.2.13
  • 2.0.77
  • 2.2.13

July 08, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.110-debian10, 2.0.110-rocky8, 2.0.110-ubuntu18
  • 2.1.58-debian11, 2.1.58-rocky8, 2.1.58-ubuntu20, 2.1.58-ubuntu20-arm
  • 2.2.24-debian12, 2.2.24-rocky9, 2.2.24-ubuntu22

July 05, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.68
  • 1.2.12
  • 2.0.76
  • 2.2.12

July 03, 2024

Added Cloud Profiler support in Dataproc Serverless for Spark. Enable profiling via the dataproc.profiling.enabled=true property and configure it via dataproc.profiling.name=<PROFILE_NAME>

New Dataproc on Compute Engine subminor image versions:

  • 2.0.109-debian10, 2.0.109-rocky8, 2.0.109-ubuntu18
  • 2.1.57-debian11, 2.1.57-rocky8, 2.1.57-ubuntu20, 2.1.57-ubuntu20-arm
  • 2.2.23-debian12, 2.2.23-rocky9, 2.2.23-ubuntu22

Dataproc on Compute Engine: Apache Hadoop upgraded to version 3.2.4 in image version 2.0 starting with image version 2.0.109.

June 28, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.108-debian10, 2.0.108-rocky8, 2.0.108-ubuntu18
  • 2.1.56-debian11, 2.1.56-rocky8, 2.1.56-ubuntu20, 2.1.56-ubuntu20-arm
  • 2.2.22-debian12, 2.2.22-rocky9, 2.2.22-ubuntu22

Backported fixes for HIVE-25958 and HIVE-20220 (new configuration hive.groupby.enable.deterministic.distribution=false/true).

June 26, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.67
  • 1.2.11
  • 2.0.75
  • 2.2.11

Dataproc Serverless for Spark: To fix compatibility with open table formats (Apache Iceberg, Apache Hudi and Delta Lake), the ANTLR version downgraded from 4.13.1 to 4.9.3 in Dataproc Serverless for Spark runtime versions 1.2 and 2.2.

June 25, 2024

The Dataproc Component Gateway is now activated by default when you create a Dataproc on Compute Engine cluster using the Google Cloud console.

June 24, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.107-debian10, 2.0.107-rocky8, 2.0.107-ubuntu18
  • 2.1.55-debian11, 2.1.55-rocky8, 2.1.55-ubuntu20, 2.1.55-ubuntu20-arm
  • 2.2.21-debian12, 2.2.21-rocky9, 2.2.21-ubuntu22

June 21, 2024

Dataproc Serverless for Spark: To fix compatibility with open table formats (Apache Iceberg, Apache Hudi and Delta Lake), the ANTLR version will be downgraded from 4.13.1 to 4.9.3 in Dataproc Serverless for Spark runtime versions 1.2 and 2.2 on June 26, 2024.

June 20, 2024

Dataproc Serverless for Spark: Spark runtime version 2.2 will become the default Dataproc Serverless for Spark runtime version on September 6, 2024.

New Dataproc Serverless for Spark runtime versions:

  • 1.1.66
  • 1.2.10
  • 2.0.74
  • 2.2.10

June 13, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.106-debian10, 2.0.106-rocky8, 2.0.106-ubuntu18
  • 2.1.54-debian11, 2.1.54-rocky8, 2.1.54-ubuntu20, 2.1.54-ubuntu20-arm
  • 2.2.20-debian12, 2.2.20-rocky9, 2.2.20-ubuntu22

New Dataproc Serverless for Spark runtime versions:

  • 1.1.65
  • 1.2.9
  • 2.0.73
  • 2.2.9

Dataproc Serverless for Spark: Upgraded Spark BigQuery connector to version 0.36.3 in the latest 1.2 and 2.2 Dataproc Serverless for Spark runtime versions.

Support configuration to prevent HiveMetaStore metrics expensive database queries. To prevent expensive queries during HiveMetaStore startup, set Hive property metastore.initial.metadata.count.enabled to false.

June 11, 2024

The Apache Spark in BigQuery feature is available in Private Preview. This feature lets you create a Spark session in a BigQuery notebook that you can use to develop and submit PySpark code from BigQuery. To access this feature, fill in and submit the Dataproc Preview access request form.

June 06, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.105-debian10, 2.0.105-rocky8, 2.0.105-ubuntu18
  • 2.1.53-debian11, 2.1.53-rocky8, 2.1.53-ubuntu20, 2.1.53-ubuntu20-arm
  • 2.2.19-debian12, 2.2.19-rocky9, 2.2.19-ubuntu22

Dataproc on Compute Engine: When creating a cluster with the latest Dataproc on Compute Engine image versions, the secondary worker boot disk type now defaults to the primary worker boot disk type, which is pd-standard if the primary worker boot disk type is not specified.

June 05, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.64
  • 1.2.8
  • 2.0.72
  • 2.2.8

June 03, 2024

Dataproc on Compute Engine: Update restartable job error messages to include job IDs.

Dataproc Serverless for Spark: Automatically apply goog-dataproc-session-id, goog-dataproc-session-uuid and goog-dataproc-location labels for a session resource.

May 30, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.104-debian10, 2.0.104-rocky8, 2.0.104-ubuntu18
  • 2.1.52-debian11, 2.1.52-rocky8, 2.1.52-ubuntu20, 2.1.52-ubuntu20-arm
  • 2.2.18-debian12, 2.2.18-rocky9, 2.2.18-ubuntu22

New Dataproc Serverless for Spark runtime versions:

  • 1.1.63
  • 1.2.7
  • 2.0.71
  • 2.1.50
  • 2.2.7

Dataproc Serverless for Spark: Subminor version 2.1.50 is the last release of runtime version 2.1, which will no longer be supported and will not receive new releases.

Dataproc Serverless for Spark: Removed Spark data lineage support for runtime version 1.2.

Dataproc Serverless for Spark: Enabled Spark checkpoint (spark.checkpoint.compress) and RDD (spark.rdd.compress) compression in the latest 1.2 and 2.2 runtime versions.

May 23, 2024

Blocklisted the following Dataproc on Compute Engine subminor image versions:

  • 2.0.103-debian10, 2.0.103-rocky8, 2.0.103-ubuntu18
  • 2.1.51-debian11, 2.1.51-rocky8, 2.1.51-ubuntu20, 2.1.51-ubuntu20-arm
  • 2.2.17-debian12, 2.2.17-rocky9, 2.2.17-ubuntu22

May 22, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.62
  • 1.2.6
  • 2.0.70
  • 2.1.49
  • 2.2.6

Upgraded Spark BigQuery connector to version 0.36.2 in the latest 1.2 and 2.2 Dataproc Serverless for Spark runtime versions.

May 16, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.102-debian10, 2.0.102-rocky8, 2.0.102-ubuntu18

  • 2.1.50-debian11, 2.1.50-rocky8, 2.1.50-ubuntu20, 2.1.50-ubuntu20-arm

  • 2.2.16-debian12, 2.2.16-rocky9, 2.2.16-ubuntu22

Anaconda's default channel is disabled for package installations on Dataproc on Compute Engine.

May 09, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.101-debian10, 2.0.101-rocky8, 2.0.101-ubuntu18

  • 2.1.49-debian11, 2.1.49-rocky8, 2.1.49-ubuntu20, 2.1.49-ubuntu20-arm

  • 2.2.15-debian12, 2.2.15-rocky9, 2.2.15-ubuntu22

May 08, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.61
  • 1.2.5
  • 2.0.69
  • 2.1.48
  • 2.2.5

May 06, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.100-debian10, 2.0.100-rocky8, 2.0.100-ubuntu18
  • 2.1.48-debian11, 2.1.48-rocky8, 2.1.48-ubuntu20, 2.1.48-ubuntu20-arm
  • 2.2.14-debian12, 2.2.14-rocky9, 2.2.14-ubuntu22

Dataproc on Compute Engine:

May 01, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.60
  • 1.2.4
  • 2.0.68
  • 2.1.47
  • 2.2.4

Dataproc Serverless for Spark:

  • Upgraded Spark RAPIDS to version 24.04.0 in 1.2 and 2.2 Dataproc Serverless for Spark runtimes.

When you submit a Dataproc Serverless Batch with a CMEK key:

  • In addition to encrypting disk and Cloud Storage data, Dataproc Serverless will use your CMEK to also encrypt batch job arguments. This change will require you to do the following:
  • batches.list will return an unreachable field that lists any batches with job arguments that couldn't be decrypted. You can issue a batches.get request to obtain more information on an unreachable batch.
  • Multi-regional and cross-regional CMEKs will no longer be permitted. The key (CMEK) must be located in the same location as the encrypted resource. For example, the CMEK used to encrypt a batch that runs in the us-central1 region must also be located in the us-central1 region.

April 29, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.99-debian10, 2.0.99-rocky8, 2.0.99-ubuntu18
  • 2.1.47-debian11, 2.1.47-rocky8, 2.1.47-ubuntu20, 2.1.47-ubuntu20-arm
  • 2.2.13-debian12, 2.2.13-rocky9, 2.2.13-ubuntu22

April 26, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.59
  • 1.2.3
  • 2.0.67
  • 2.1.46
  • 2.2.3

April 21, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.98-debian10, 2.0.98-rocky8, 2.0.98-ubuntu18
  • 2.1.46-debian11, 2.1.46-rocky8, 2.1.46-ubuntu20, 2.1.46-ubuntu20-arm
  • 2.2.12-debian12, 2.2.12-rocky9, 2.2.12-ubuntu22

April 20, 2024

Announcing Dataproc Workflow Templates supports the CMEK organization policy.

April 18, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.58
  • 1.2.2
  • 2.0.66
  • 2.1.45
  • 2.2.2

Set the soft delete policy of newly created Dataproc staging and temp Cloud Storage buckets to 0 days.

Updated the default autoscaling V2 cool-down time from 2m to 1m to reduce scaling latency.

Fixed a bug where Dataproc Serverless sessions that live longer than 48 hours are underbilled.

April 09, 2024

Dataproc Serverless for Spark: The preview release of Advanced troubleshooting, including Gemini-assisted troubleshooting, is now available for Spark workloads submitted with the following or later-released runtime versions:

  • 1.1.55
  • 1.2.0-RC1
  • 2.0.63
  • 2.1.42
  • 2.2.0-RC15

Dataproc Serverless for Spark: Announcing the preview release of Autotuning Spark workloads.

April 04, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.57
  • 1.2.1
  • 2.0.65
  • 2.1.44
  • 2.2.1

Added bigframes Python package by default in the Dataproc Serverless for Spark runtime versions 1.2 and 2.2

April 02, 2024

The following previously released sub-minor versions of Dataproc on Compute Engine images have been rolled back and can only be used when updating existing clusters that already use them:

  • 2.0.97-debian10, 2.0.97-rocky8, 2.0.97-ubuntu18
  • 2.1.45-debian11, 2.1.45-rocky8, 2.1.45-ubuntu20, 2.1.45-ubuntu20-arm
  • 2.2.11-debian12, 2.2.11-rocky9, 2.2.11-ubuntu22

March 29, 2024

Dataproc Serverless for Spark: runtime version 2.2 will become the default Dataproc Serverless for Spark runtime version on May 3, 2024.

Note: This announcement was updated in the April 19, 2024 release note.

March 28, 2024

Note: the above subminor image versions were rolled back on April 2, 2024

Dataproc on Compute Engine: New Hadoop Google Secret Manager Credential Provider feature introduced in latest Dataproc on Compute Engine 2.0 image versions.

March 27, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.56
  • 1.2.0
  • 2.0.64
  • 2.1.43
  • 2.2.0

Announcing the General Availability (GA) release of Dataproc Serverless for Spark runtime versions 1.2 and 2.2, which include the following components:

  • Spark 3.5.1
  • BigQuery Spark Connector 0.36.1
  • Cloud Storage Connector 3.0.0
  • Conda 24.1
  • Java 17
  • Python 3.12
  • R 4.3
  • Scala 2.12 (1.2 runtime) and Scala 2.13 (2.2 runtime)

Dataproc Serverless for Spark:

  • Upgraded Spark to version 3.5.1 in the latest 1.2 and 2.2 runtimes.
  • Upgraded Conda to version 24.1 in the latest 1.2 and 2.2 runtimes.
  • Upgraded Spark BigQuery connector to version 0.36.1 in the latest 1.2 and 2.2 runtimes.

March 21, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.96-debian10, 2.0.96-rocky8, 2.0.96-ubuntu18
  • 2.1.44-debian11, 2.1.44-rocky8, 2.1.44-ubuntu20, 2.1.44-ubuntu20-arm
  • 2.2.10-debian12, 2.2.10-rocky9, 2.2.10-ubuntu22

March 20, 2024

Announcing the Preview release of Dataproc Serverless for Spark 1.2 runtime:

  • Spark 3.5.0
  • BigQuery Spark Connector 0.35.1
  • Cloud Storage Connector 3.0.0
  • Conda 23.11
  • Java 17
  • Python 3.12
  • R 4.3
  • Scala 2.12

New Dataproc Serverless for Spark runtime versions:

  • 1.1.55
  • 1.2.0-RC1
  • 2.0.63
  • 2.1.42
  • 2.2.0-RC15

Dataproc Serverless for Spark:

  • Upgraded Spark RAPIDS plugin to version 24.2.0 in the latest runtimes.
  • Upgraded Spark to version 3.3.4 in the latest 1.1 and 2.0 runtimes.
  • Backported SPARK-44198 in the latest 1.2 and 2.2 runtimes.

March 14, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.95-debian10, 2.0.95-rocky8, 2.0.95-ubuntu18
  • 2.1.43-debian11, 2.1.43-rocky8, 2.1.43-ubuntu20, 2.1.43-ubuntu20-arm
  • 2.2.9-debian12, 2.2.9-rocky9, 2.2.9-ubuntu22

New Dataproc Serverless for Spark runtime versions:

  • 1.1.54
  • 2.0.62
  • 2.1.41
  • 2.2.0-RC14

Added the bigframes (BigQuery DataFrames) Python package in the Dataproc Serverless for Spark 2.1 runtime.

March 07, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.53
  • 2.0.61
  • 2.1.40
  • 2.2.0-RC13

Dataproc Serverless for Spark: Upgraded Cloud Storage connector to 2.2.20 version in the latest 1.1, 2.0, and 2.1 runtimes.

March 06, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.94-debian10, 2.0.94-rocky8, 2.0.94-ubuntu18
  • 2.1.42-debian11, 2.1.42-rocky8, 2.1.42-ubuntu20, 2.1.42-ubuntu20-arm
  • 2.2.8-debian12, 2.2.8-rocky9, 2.2.8-ubuntu22

Dataproc on Compute Engine: Upgraded Cloud Storage connector version to 2.2.20 for 2.0 and 2.1 images.

Dataproc on Compute Engine: Mounted Java cacerts into containers by default when the Docker-on-YARN feature is enabled.

March 04, 2024

Dataproc Serverless for Spark: Extended Spark metrics collected for a batch now include executor:resultSize, executor:shuffleBytesWritten, and executor:shuffleTotalBytesRead.

February 29, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.52
  • 2.0.60
  • 2.1.39
  • 2.2.0-RC12

February 28, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.93-debian10, 2.0.93-rocky8, 2.0.93-ubuntu18
  • 2.1.41-debian11, 2.1.41-rocky8, 2.1.41-ubuntu20, 2.1.41-ubuntu20-arm
  • 2.2.7-debian12, 2.2.7-rocky9, 2.2.7-ubuntu22

Dataproc on Compute Engine: The new Secret Manager credential provider feature is available in the latest 2.1 image versions.

Dataproc on Compute Engine:

  • Upgraded Zookeeper to 3.8.3 for Dataproc 2.2.
  • Upgraded ORC for Hive to 1.15.13 for Dataproc 2.1.
  • Upgraded ORC for Spark to 1.7.10 for Dataproc 2.1.
  • Extended expiry for the internal Knox Gateway certificate from one year to five years from cluster creation for Dataproc images 2.0, 2.1, and 2.2.

Dataproc on Compute Engine: Fixed ZooKeeper startup failures in image 2.2 HA (High Availability) clusters that use fully qualified hostnames.

February 22, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.51
  • 2.0.59
  • 2.1.38
  • 2.2.0-RC11

February 16, 2024

Dataproc on Compute Engine: The internalIpOnly cluster configuration setting now defaults to true for clusters created with 2.2 image versions. Also see Create a Dataproc cluster with internal IP addresses only.

February 15, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.50
  • 2.0.58
  • 2.1.37
  • 2.2.0-RC10

Dataproc Serverless for Spark: Spark Lineage is available for Dataproc Serverless for Spark 1.1 runtime.

February 08, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.92-debian10, 2.0.92-rocky8, 2.0.92-ubuntu18
  • 2.1.40-debian11, 2.1.40-rocky8, 2.1.40-ubuntu20, 2.1.40-ubuntu20-arm
  • 2.2.6-debian12, 2.2.6-rocky9, 2.2.6-ubuntu22

Dataproc on Compute Engine Ranger Cloud Storage enhancement:

  • Enabled downscoping
  • Added caching of tokens in local cache

Both settings are configurable and can be enabled by customers: see Use Ranger with caching and downscoping .

Dataproc on Compute Engine: The new Secret Manager credential provider feature is available in the latest 2.2 image versions.

Dataproc on Compute Engine: Backported patch for HADOOP-18652.

New Dataproc Serverless for Spark runtime versions:

  • 1.1.49
  • 2.0.57
  • 2.1.36
  • 2.2.0-RC9

Dataproc Serverless for Spark: Backported patch for HADOOP-18652.

February 02, 2024

Dataproc on Compute Engine: Bucket ttl validation now also runs for buckets created by Dataproc.

Dataproc on Compute Engine: Added a warning during cluster creation if the cluster Cloud Storage staging bucket is using the legacy fine-grained/ACL IAM configuration instead of the recommended Uniform bucket-level access controls.

Dataproc Serverless for Spark: When dynamic allocation is enabled, the initial executor number is determined by max of spark.dynamicAllocation.initialExecutors and spark.executor.instances.

February 01, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.91-debian10, 2.0.91-rocky8, 2.0.91-ubuntu18
  • 2.1.39-debian11, 2.1.39-rocky8, 2.1.39-ubuntu20, 2.1.39-ubuntu20-arm
  • 2.2.5-debian12, 2.2.5-rocky9, 2.2.5-ubuntu22

New Dataproc Serverless for Spark runtime versions:

  • 1.1.48
  • 2.0.56
  • 2.1.35
  • 2.2.0-RC8

Dataproc on Compute Engine: Backported patches for HIVE-21214, HIVE-23154, HIVE-23354 and HIVE-23614.

January 31, 2024

Dataproc is now available in the africa-south1 region (Johannesburg, South Africa).

The GitHub Ops Agent initialization action installs the Ops Agent on a Dataproc cluster, and provides metrics similar to the metrics that were enabled with the --metric-sources=monitoring-agent-defaults setting available for use with Dataproc images versions prior to version 2.2.

January 25, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.47
  • 2.0.55
  • 2.1.34
  • 2.2.0-RC7

January 24, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.90-debian10, 2.0.90-rocky8, 2.0.90-ubuntu18
  • 2.1.38-debian11, 2.1.38-rocky8, 2.1.38-ubuntu20, 2.1.38-ubuntu20-arm
  • 2.2.4-debian12, 2.2.4-rocky9, 2.2.4-ubuntu22

Backport HIVE-19568: Active/Passive HiveServer2 HA: Disallow direct connection to passive instance.

Backport HIVE-27715: Remove ThreadPoolExecutorWithOomHook.

January 19, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.89-debian10, 2.0.89-rocky8, 2.0.89-ubuntu18
  • 2.1.37-debian11, 2.1.37-rocky8, 2.1.37-ubuntu20, 2.1.37-ubuntu20-arm
  • 2.2.3-debian12, 2.2.3-rocky9, 2.2.3-ubuntu22

Dataproc on Compute Engine: The default yarn.nm.liveness-monitor.expiry-interval-ms Hadoop YARN setting has been changed in the latest image versions from 15000 (15 seconds) to 120000 (2 minutes).

Dataproc on Compute Engine: Upgraded Cloud Storage connector version to 2.2.19 in the latest 2.0 and 2.1 images.

Dataproc on Compute Engine: Upgraded Miniconda to 23.11, Python to 3.11, and curl to 8.5 to fix CVE-2023-38545 in the latest 2.2 images.

Dataproc on Compute Engine: Fixed the gsutil: command not found error in the latest Ubuntu images.

Dataproc on Compute Engine: Fixed Trino startup issue in the latest 2.2 images.

New Dataproc Serverless for Spark runtime versions:

  • 1.1.46
  • 2.0.54
  • 2.1.33
  • 2.2.0-RC6

Dataproc Serverless for Spark: Upgraded Cloud Storage connector to 2.2.19 version in the latest 1.1, 2.0, and 2.1 runtimes.

January 17, 2024

Beginning March 31, 2024, when you submit a Dataproc Serverless Batch with a CMEK key:

  • In addition to encrypting disk and Cloud Storage data, Dataproc Serverless will use your CMEK to also encrypt batch job arguments. This change will require that you assign the Cloud KMS CryptoKey Encrypter/Decrypter and the Service Usage Consumer role to the Dataproc Service Agent service account.
  • batches.list will return an unreachable field that lists any batches with job arguments that couldn't be decrypted. You can issue a batches.get request to obtain more information on an unreachable batch.
  • Multi-regional and cross-regional CMEKs will no longer be permitted. The key (CMEK) must be located in the same location as the encrypted resource. For example, the CMEK used to encrypt a batch that runs in the us-central1 region must also be located in the us-central1 region.

January 15, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.45
  • 2.0.53
  • 2.1.32
  • 2.2.0-RC5

Dataproc Serverless for Spark:

  • Upgraded Spark RAPIDS to version 23.12.1

  • Upgraded the following components to the following versions in the latest 2.2 runtime:

    • Spark BigQuery connector version 0.35.0
    • Cloud Storage connector version 3.0.0
    • Conda version 23.11

January 05, 2024

New Dataproc Serverless for Spark runtime versions:

  • 1.1.44
  • 2.0.52
  • 2.1.31
  • 2.2.0-RC4

January 04, 2024

The following previously released sub-minor versions of Dataproc images have been rolled back and can only be used when updating existing clusters that already use them:

  • 2.0.88-debian10, 2.0.88-rocky8, 2.0.88-ubuntu18
  • 2.1.36-debian11, 2.1.36-rocky8, 2.1.36-ubuntu20, 2.1.36-ubuntu20-arm
  • 2.2.2-debian12, 2.2.2-rocky9, 2.2.2-ubuntu22

January 02, 2024

New Dataproc on Compute Engine subminor image versions:

  • 2.0.88-debian10, 2.0.88-rocky8, 2.0.88-ubuntu18
  • 2.1.36-debian11, 2.1.36-rocky8, 2.1.36-ubuntu20, 2.1.36-ubuntu20-arm

  • 2.2.2-debian12, 2.2.2-rocky9, 2.2.2-ubuntu22

  • Rollback Notice: See the January 4, 2024 release note rollback notice.

Dataproc on Compute Engine: Changed the Hive Server2 and MetaStore maximum default JVM heap size to 32GiB. Previously, the limit was set to 1/4 of total node memory, which could be too large on large-memory machines.

Dataproc on Compute Engine: Backported the patch for YARN-10975 in the latest 2.0 images.

December 21, 2023

New Dataproc Serverless for Spark runtime versions:

  • 1.1.43
  • 2.0.51
  • 2.1.30
  • 2.2.0-RC3

December 18, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.87-debian10, 2.0.87-rocky8, 2.0.87-ubuntu18
  • 2.1.35-debian11, 2.1.35-rocky8, 2.1.35-ubuntu20, 2.1.35-ubuntu20-arm
  • 2.2.1-debian12, 2.2.1-rocky9, 2.2.1-ubuntu22

December 14, 2023

New Dataproc Serverless for Spark runtime versions:

  • 1.1.42
  • 2.0.50
  • 2.1.29
  • 2.2.0-RC2

Added the google-cloud-secret-manager Python package in the latest Dataproc Serverless for Spark runtimes.

December 11, 2023

Announcing the GA release of Dataproc on Compute Engine image version 2.2 :

  • 2.2.0-debian12, 2.2.0-rocky9, 2.2.0-ubuntu22

The 2.2.0 release includes the following components:

  • Debian-12 / Ubuntu-2204 / RockyLinux 9
  • Apache Hadoop 3.3.6
  • Apache Spark 3.5.0
  • Spark-BigQuery Connector 0.34.0
  • Cloud Storage Connector 3.0.0
  • Trino 432
  • Apache Flink 1.17.0
  • Apache Ranger 2.4.0
  • Apache Solr 9.2.1
  • R 4.2
  • Hue 4.11.0
  • JupyterLab Notebook 3.6

Monitoring-agent-defaults metrics are not available in Dataproc on Compute Engine image version 2.2 clusters unless the Ops Agent is installed. Other metrics for Dataproc provided components will continue to work.

Blocklisted the following Dataproc on Compute Engine Images due to issue with increase in startup time:

  • 2.0.86-debian10, 2.0.86-rocky8, 2.0.86-ubuntu18
  • 2.1.34-debian11, 2.1.34-rocky8, 2.1.34-ubuntu20, 2.1.34-ubuntu20-arm

December 06, 2023

Announcing the Preview release of Dataproc Serverless for Spark 2.2 runtime:

  • Spark 3.5.0
  • BigQuery Spark Connector 0.34.0
  • Cloud Storage Connector 3.0.0-RC1
  • Conda 23.10
  • Java 17
  • Python 3.12
  • R 4.3
  • Scala 2.13

New Dataproc Serverless for Spark runtime versions:

  • 1.1.41
  • 2.0.49
  • 2.1.28
  • 2.2.0-RC1

December 04, 2023

Added the Confidential Computing option on the "Manage Security" panel on the "Create a Dataproc cluster on Compute Engine" page in the Google Cloud console.

New Dataproc on Compute Engine subminor image versions:

  • 2.0.85-debian10, 2.0.85-rocky8, 2.0.85-ubuntu18
  • 2.1.33-debian11, 2.1.33-rocky8, 2.1.33-ubuntu20, 2.1.33-ubuntu20-arm

Updated the Zookeeper component version from 3.8.0 to 3.8.3 in the latest Dataproc on Compute Engine 2.1 image version.

Fixed Dataproc Hub issue in latest Dataproc on Compute Engine 2.1 image.

Backported HIVE-21698 in Hive 3.1.3 component in latest Dataproc on Compute Engine image versions.

December 01, 2023

The Cloud Storage connector has been upgraded to version 2.2.18 in all Dataproc Serverless for Spark runtimes.

November 17, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.84-debian10, 2.0.84-rocky8, 2.0.84-ubuntu18
  • 2.1.32-debian11, 2.1.32-rocky8, 2.1.32-ubuntu20, 2.1.32-ubuntu20-arm
  • 2.2.0-RC3-debian11/-ubuntu22/-rocky9

Upgraded the Cloud Storage connector version to 2.2.18 in the latest 2.0 and 2.1 Dataproc on Compute Engine image versions.

In the Flink component in the latest Dataproc on Compute Engine 2.1 image version, added the following java-storage client properties:

Fixed a regression in the Zeppelin websocket rules that caused a websocket error in Zeppelin notebooks.

The Python kernel does not work in Zeppelin on the Dataproc on Compute Engine 2.1 image version. Other kernels are not impacted.

The Zeppelin REST API does not work (drops query parameters) on Dataproc on Compute Engine 2.0 and 2.1 image versions via the Component Gateway. Other Zeppelin interactions can also break as a result of dropped query parameters.

November 15, 2023

You can use CMEK (Customer Managed Encrytion Keys) with encrypted Dataproc cluster data, incuding persistent disk data, job arguments and queries submitted with Dataproc jobs, and cluster data saved in the cluster Dataproc staging bucket. See Use CMEK with cluster data for more information.

November 10, 2023

Announcing the General Availability (GA) release of Dataproc Jupyter Plugin and its availability in Vertex AI Workbench instance notebooks.

New Dataproc on Compute Engine subminor image versions:

  • 2.0.83-debian10, 2.0.83-rocky8, 2.0.83-ubuntu18
  • 2.1.31-debian11, 2.1.31-rocky8, 2.1.31-ubuntu20, 2.1.31-ubuntu20-arm

November 08, 2023

Announcing the release of Workflow Template CMEK (Customer Managed Encryption Key) encryption. Use this feature to apply CMEK encryption to workflow template job arguments. For example, when this feature is enabled, the query string of a workflow template SparkSQL job is encrypted using CMEK.

You can now use Dataproc Serverless autoscaling V2 to help you manage Dataproc Serverless workloads, improve workload performance, and save costs.

November 07, 2023

Set spark.shuffle.mapOutput.minSizeForBroadcast=128m to fix SPARK-38101 when Dataproc Serverless Spark dynamic allocation is enabled.

November 01, 2023

Announcing the Preview release of Dataproc Flexible VMs. This feature lets you specify prioritized lists of secondary worker VM types that Dataproc will select from when creating your cluster. Dataproc will select the VM type with sufficient available capacity while taking quotas and reservations into account.

October 30, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.82-debian10, 2.0.82-rocky8, 2.0.82-ubuntu18
  • 2.1.30-debian11, 2.1.30-rocky8, 2.1.30-ubuntu20, 2.1.30-ubuntu20-arm

Added spark.dataproc.scaling.version=2 config to let customers control the Dataproc Serverless for Spark autoscaling version.

Increased the TTL for Dataproc on Compute Engine custom images from 60 days to 365 days.

Fixed Knox rewrite rules for Zeppelin URLs in some cases in the latest 2.0 and 2.1 Dataproc on Compute Engine image versions.

October 27, 2023

October 25, 2023

October 23, 2023

Dataproc on Compute Engine: Dataproc now collects the dataproc.googleapis.com/job/yarn/vcore_seconds and dataproc.googleapis.com/job/yarn/memory_seconds job-level resource attribution metrics to track YARN application vcore and memory usage during job execution. These metrics are collected by default and are not chargeable to customers.

Dataproc on Compute Engine: Dataproc now collects a dataproc.googleapis.com/node/yarn/nodemanager/health health metric to track the health of individual YARN node managers running on VMs. This metric is written against the gce_instance monitored resource to help you find suspect nodes. It is collected by default and is not chargeable to customers.

Dataproc on Compute Engine: Properties dataproc:agent.ha.enabled and dataproc:componentgateway.ha.enabled now default to true to provide high availability for the Dataproc Agent and Component Gateway.

October 13, 2023

October 12, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.80-debian10, 2.0.80-rocky8, 2.0.80-ubuntu18
  • 2.1.28-debian11, 2.1.28-rocky8, 2.1.28-ubuntu20, 2.1.28-ubuntu20-arm

October 09, 2023

October 06, 2023

New Dataproc on Compute Engine image version 2.2 is available for preview with upgraded components.

New Dataproc on Compute Engine subminor image versions:

  • 2.0.79-debian10, 2.0.79-rocky8, 2.0.79-ubuntu18
  • 2.1.27-debian11, 2.1.27-rocky8, 2.1.27-ubuntu20, 2.1.27-ubuntu20-arm
  • 2.2.0-RC2-debian11, 2.2.0-RC2-rocky9, 2.2.0-RC2-ubuntu22

Upgraded Hadoop version from 3.3.3 to 3.3.6 in the latest Dataproc on Compute Engine 2.1 image version.

Upgraded the Cloud Storage connector version to 2.2.17 in the latest Dataproc Serverless for Spark runtimes.

Added the gs.http.connect-timeout and gs.http.read-timeout properties in Flink to set the connection timeout and read timeout for java-storage client in the latest Dataproc on Compute Engine 2.1 image version.

Added the gs.filesink.entropy.enabled property in Flink to enable entropy injection in filesink Cloud Storage path in the latest Dataproc on Compute Engine 2.1 image version.

September 28, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.78-debian10, 2.0.78-rocky8, 2.0.78-ubuntu18
  • 2.1.26-debian11, 2.1.26-rocky8, 2.1.26-ubuntu20, 2.1.26-ubuntu20-arm

Upgraded the Cloud Storage connector version to 2.2.17 in the latest 2.0 and 2.1 Dataproc on Compute Engine image versions.

Upgraded Hive version from 3.1.2 to 3.1.3 in the latest Dataproc on Compute Engine 2.0 image version.

September 22, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.77-debian10, 2.0.77-rocky8, 2.0.77-ubuntu18
  • 2.1.25-debian11, 2.1.25-rocky8, 2.1.25-ubuntu20, 2.1.25-ubuntu20-arm

In the latest Dataproc on Compute Engine 2.0 and 2.1 image versions, unset the CLOUDSDK_PYTHON variable to allow the gcloud command-line tool to use its bundled Python interpreter.

Fixed Jupyter notebooks bug that made Scala compilation errors invisible with the Toree kernel in Dataproc on Compute Engine 2.1 images.

September 19, 2023

Dataproc is now available in the me-central2 region (Dammam, Saudi Arabia).

September 15, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.76-debian10, 2.0.76-rocky8, 2.0.76-ubuntu18
  • 2.1.24-debian11, 2.1.24-rocky8, 2.1.24-ubuntu20, 2.1.24-ubuntu20-arm

Scala has been upgraded to version 2.12.18 and Apache Tez has been upgraded to version 0.10.2 in Dataproc on Compute Engine 2.1 images.

September 13, 2023

Announcing the Private Preview release of the Dataproc on Compute Engine Flink Jobs resource. During Private Preview, you can contact your Google Cloud Sales representative to have your project(s) added to an allowlist to allow you to submit Flink jobs to the Dataproc on Compute Engine service.

September 12, 2023

The dataproc.diagnostics.enabled property is now avaiable to enable running diagnostics on Dataproc Serverless for Spark. The existing spark.dataproc.diagnostics.enabled property will be deprecated for use with newer runtimes.

September 08, 2023

Dataproc Auto zone placement for clusters is now available in the Google Cloud console by selecting the "Any" option for the cluster zone.

New Dataproc on Compute Engine subminor image versions:

  • 2.0.75-debian10, 2.0.75-rocky8, 2.0.75-ubuntu18
  • 2.1.23-debian11, 2.1.23-rocky8, 2.1.23-ubuntu20, 2.1.23-ubuntu20-arm

The Apache Spark version has been upgraded from 3.3.0 to 3.3.2 in Dataproc on Compute Engine 2.1 images.

September 04, 2023

Announcing the General Availability (GA) release of Data Lineage for Dataproc, which captures data transformations (lineage events) in Dataproc Spark jobs, and publishes them to Dataplex Lineage.

Dataproc Serverless Interactive sessions detail and list pages are now available in the Google Cloud console.

August 29, 2023

Announcing the Preview release of Dataproc Serverless for Spark Interactive sessions and the Dataproc Jupyter Plugin.

August 25, 2023

August 23, 2023

Fixed a Dataproc Serverless issue where Spark batches failed with unhelpful error messages.

August 22, 2023

Dataproc is now available in the europe-west10 region (Berlin).

August 17, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.74-debian10, 2.0.74-rocky8, 2.0.74-ubuntu18
  • 2.1.22-debian11, 2.1.22-rocky8, 2.1.22-ubuntu20, 2.1.22-ubuntu20-arm

Backported the patches for HIVE-20618 in the new Dataproc on Compute Engine 2.0 and 2.1 images.

August 11, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.73-debian10, 2.0.73-rocky8, 2.0.73-ubuntu18
  • 2.1.21-debian11, 2.1.21-rocky8, 2.1.21-ubuntu20, 2.1.21-ubuntu20-arm

Added new Dataproc Serverless Templates for batch workload creation:

  • Cloud Spanner to Cloud Storage
  • Cloud Storage to JDBC
  • Cloud Storage to Cloud Storage
  • Hive to BigQuery
  • JDBC to Cloud Spanner
  • JDBC to JDBC
  • Pub/Sub to Cloud Storage

Improved the reliability of Dataproc Serverless compute node initialization with a Premium disk tier option.

August 07, 2023

Added a dataproc:dataproc.cluster.caching.enabled flag to enable and disable Dataproc on Compute Engine cluster caching. The flag is false by default. Use this feature with the latest Dataproc on Compute Engine images.

August 06, 2023

The following previously released sub-minor versions of Dataproc on Compute Engine images unintentionally reverted several dependency library versions. This caused a risk of backward-incompatibility for some workloads.

These sub-minor versions have been rolled back, and can only be used when updating existing clusters that already use them:

  • 2.0.71-debian10, 2.0.71-rocky8, 2.0.71-ubuntu18
  • 2.1.19-debian11, 2.1.19-rocky8, 2.1.19-ubuntu20, 2.1.19-ubuntu20-arm

August 05, 2023

New Dataproc on Compute Engine image versions:

  • 2.0.72-debian10, 2.0.72-rocky8, 2.0.72-ubuntu18
  • 2.1.20-debian11, 2.1.20-rocky8, 2.1.20-ubuntu20, 2.1.20-ubuntu20-arm

Upgraded Hudi to 0.12.3 and added the BigQuery Sync tool as part of the Hudi optional component.

Downgraded Cloud Storage connector version to 2.2.15 in all Dataproc on Compute Engine image versions to prevent potential performance regression.

Backported ZEPPELIN-5434 to image 2.1 to fix CVE-2022-2048.

Backported the patches for HIVE-22170 and HIVE-22331.

August 03, 2023

Downgraded Cloud Storage connector to 2.2.15 version in all Dataproc Serverless for Spark runtimes to prevent potential performance regression.

July 30, 2023

New Dataproc on Compute Engine image versions:

  • 2.0.71-debian10, 2.0.72-rocky8, 2.0.72-ubuntu18
  • 2.1.19-debian11, 2.1.20-rocky8, 2.1.20-ubuntu20, 2.1.20-ubuntu20-arm

Note: The above image versions were rolled back. See the August 6, 2023 release note

The Maximum total memory per core for Dataproc Serverless Premium compute tiers has increased to 24576m (7424m for Standard compute tiers unchanged). See Dataproc Serverless Resource allocation properties.

July 28, 2023

July 26, 2023

Clusters cannot be created with a driver node group if the cluster image version is older than 2.0.57 or 2.1.5, or if the permissions for the staging bucket are missing.

Added recommendation details in Autoscaler Stackdriver logs for the CANCEL and DO_NOT_CANCEL recommendations.

July 21, 2023

New Dataproc on Compute Engine image versions, which includes a 2.1.18-ubuntu20-arm image that supports ARM machine types:

  • 2.0.70-debian10, 2.0.70-rocky8, 2.0.70-ubuntu18
  • 2.1.18-debian11, 2.1.18-rocky8, 2.1.18-ubuntu20, 2.1.18-ubuntu20-arm

Fixed a race condition in Spark startup that could lead to nodes failing to initialize when using premium disk tier.

July 14, 2023

Clusters that use a driver node group now configure YARN queues with user-limit-factor set to 2, allowing for a single user to burst to 2x utilization of capacity, which is set to 50. This achieves better resource utilization for workloads submitted by a single user.

Upgraded the Cloud Storage connector version to 2.2.16 in Dataproc Serverless for Spark runtimes.

July 10, 2023

New Dataproc on Compute Engine image versions:

  • 2.0.69-debian10, 2.0.69-rocky8, 2.0.69-ubuntu18
  • 2.1.17-debian11, 2.1.17-rocky8, 2.1.17-ubuntu20

Upgraded the Cloud Storage connector version to 2.2.16 for Dataproc on Compute Engine 2.0 and 2.1 images.

July 07, 2023

Dataproc Serverless Spark 1.1 and 2.0 runtime subminor versions can now be used 365 days after their release (instead of 90 days).

The goog-dataproc-batch-id, goog-dataproc-batch-uuid and goog-dataproc-location labels are now automatically applied to Dataproc Serverless batch resources.

Dataproc Serverless for Spark now supports updating the BigQuery connector using the dataproc.sparkBqConnector.version and dataproc.sparkBqConnector.uri properties see Use the BigQuery connector with Dataproc Serverless for Spark.

July 06, 2023

June 29, 2023

Added support for Premium compute and storage pricing tiers for Dataproc Serverless Spark workloads. Premium compute offers higher performance per core, and Premium storage offers higher throughput and IOPs. To use Premium compute and storage, set the following Spark runtime environment properties:

  • spark.dataproc.(driver|executor).compute.tier=premium
  • spark.dataproc.(driver|executor).storage.tier=premium.

June 28, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.68-debian10, 2.0.68-rocky8, 2.0.68-ubuntu18
  • 2.1.16-debian11, 2.1.16-rocky8, 2.1.16-ubuntu20

Backported ZEPPELIN-5755 to Zeppelin 0.10 in 2.1 images for Spark 3.3 support.

June 26, 2023

Added Dataproc Serverless Templates for batch creation:

  • Cloud Storage to BigQuery
  • Cloud Storage to Cloud Spanner
  • Hive to Cloud Storage
  • JDBC to BigQuery
  • JDBC to Cloud Storage

June 22, 2023

June 16, 2023

New Dataproc on Compute Engine subminor image versions:

  • 2.0.67-debian10, 2.0.67-rocky8, 2.0.67-ubuntu18
  • 2.1.15-debian11, 2.1.15-rocky8, 2.1.15-ubuntu20

Fixed a bug that caused cluster creation to fail when ATSv2 is enabled for tables that have a garbage collection policy setup other than maxversions.

June 14, 2023

June 08, 2023

June 02, 2023

Upgrade Cloud Storage connector to 2.2.14 version in Dataproc Serverless for Spark runtimes.

June 01, 2023

New sub-minor versions of Dataproc images:

  • 2.0.66-debian10, 2.0.66-rocky8, 2.0.66-ubuntu18
  • 2.1.14-debian11, 2.1.14-rocky8, 2.1.14-ubuntu20

Upgrade Cloud Storage connector version to 2.2.14 for 2.0 and 2.1 images

Backport HIVE-22891, HIVE-21660, HIVE-21915 to 2.0 images.

Backport HIVE-22891, HIVE-21660, HIVE-25520, HIVE-25521 to 2.1 images.

May 26, 2023

New sub-minor versions of Dataproc images:

  • 2.0.65-debian10, 2.0.65-rocky8, 2.0.65-ubuntu18
  • 2.1.13-debian11, 2.1.13-rocky8, 2.1.13-ubuntu20

May 24, 2023

Upgraded the Cloud Storage connector to 2.2.13 version in Dataproc on Compute Engine 2.0 and 2.1 image versions.

Unauthorized callers attempting to get, delete, or terminate non-existent Sessions will now receive a 403 response code instead of a 404 response code. This does not impact authorized callers.

Fixed Serverless history server endpoint URL when Persistent History Server (PHS) was setup without using a wildcard.

May 19, 2023

Upgraded the Cloud Storage connector to 2.2.13 version in Dataproc Serverless for Spark runtimes.

Fixed the NoClassDefFoundError for log4j class in Zeppelin BigQuery interpreter in 2.0 images.

Backported HIVE-22891 to 2.0 images.

May 18, 2023

New sub-minor versions of Dataproc images:

  • 2.0.64-debian10, 2.0.64-rocky8, 2.0.64-ubuntu18
  • 2.1.12-debian11, 2.1.12-rocky8, 2.1.12-ubuntu20

You can now use --properties=dataproc:componentgateway.ha.enabled=true to enable the Dataproc Component Gateway and Knox along with the Spark History Server (SHS) UI in HA mode.

May 11, 2023

May 05, 2023

Announcing the General Availability (GA) release of Dataproc Serverless for Spark runtime version 2.1, which includes the following components:

  • Spark 3.4.0
  • BigQuery Spark Connector 0.28.1
  • Cloud Storage Connector 2.2.11
  • Conda 23.3
  • Java 17
  • Python 3.11
  • R 4.2
  • Scala 2.13

April 28, 2023

New Dataproc Serverless for Spark runtime versions:

  • 1.1.12
  • 2.0.20
  • 2.1.0-RC8

Upgrade Spark to 3.4.0 and its dependencies in Dataproc Serverless for Spark 2.1 runtime:

  • Jetty to 9.4.51.v20230217
  • ORC to 1.8.3
  • Parquet to 1.13.0
  • Protobuf to 3.22.3

New sub-minor versions of Dataproc images:

  • 1.5.89-debian10, 1.5.89-rocky8, 1.5.89-ubuntu18
  • 2.0.63-debian10, 2.0.63-rocky8, 2.0.63-ubuntu18
  • 2.1.11-debian11, 2.1.11-rocky8, 2.1.11-ubuntu20

hive principal will be used for Hive catalog queries via presto in kerberos cluster.

April 24, 2023

Dataproc now supports the usage of cross-project service account.

Autoscaler recommendation reasoning details are available now in Cloud Logging logs.

Default batch TTL is set to 4 hours for Dataproc Serverless for Spark runtime version 2.1.

April 20, 2023

New sub-minor versions of Dataproc images:

  • 1.5.88-debian10, 1.5.88-rocky8, 1.5.88-ubuntu18
  • 2.0.62-debian10, 2.0.62-rocky8, 2.0.62-ubuntu18
  • 2.1.10-debian11, 2.1.10-rocky8, 2.1.10-ubuntu20

Running Spark jobs with the DataprocFileOutoutputCommitter is now supported. Enable the committer for Spark applications that write to a Cloud Storage destination concurrently.

April 18, 2023

Add Autoscaler recommendation reasoning details in Cloud Logging.

Dataproc on GKE SLM force delete timeout exception converted to DataprocIoException.

April 17, 2023

Announcing Dataproc General Availability (GA) support for CMEK organization policy.

April 14, 2023

New Dataproc Serverless for Spark runtime versions:

  • 1.1.11
  • 2.0.19
  • 2.1.0-RC7

Make spark user an owner for all items in the driver working directory for Dataproc Serverless for Spark workloads to fix permissions issues after Hadoop upgrade to 3.3.5.

April 06, 2023

New Dataproc Serverless for Spark runtime versions:

  • 1.1.10
  • 2.0.18
  • 2.1.0-RC6

April 04, 2023

March 30, 2023

Dataproc is now available in the me-central1 region (Doha).

March 28, 2023

New sub-minor versions of Dataproc images:

  • 1.5.87-debian10, 1.5.87-rocky8, 1.5.87-ubuntu18
  • 2.0.61-debian10, 2.0.61-rocky8, 2.0.61-ubuntu18
  • 2.1.9-debian11, 2.1.9-rocky8, 2.1.9-ubuntu20

Dataproc cluster creation now supports the pd-extreme disk type.

Dataproc on GKE now disallows update operations.

Dataproc on GKE diagnose operation now verifies that the master agent is running.

March 27, 2023

New sub-minor versions of Dataproc images:

  • 1.5.86-debian10, 1.5.86-rocky8, 1.5.86-ubuntu18
  • 2.0.60-debian10, 2.0.60-rocky8, 2.0.60-ubuntu18
  • 2.1.8-debian11, 2.1.8-rocky8, 2.1.8-ubuntu20

March 24, 2023

Upgrade Python to 3.11 and Conda to 23.1 in Dataproc Serverless for Spark runtime 2.1

March 23, 2023

Dataproc is now available in the europe-west12 region (Turin).

March 17, 2023

March 16, 2023

New sub-minor versions of Dataproc images:

  • 1.5.85-debian10, 1.5.85-rocky8, 1.5.85-ubuntu18
  • 2.0.59-debian10, 2.0.59-rocky8, 2.0.59-ubuntu18
  • 2.1.7-debian11, 2.1.7-rocky8, 2.1.7-ubuntu20
  • Upgrade Flink to 1.15.3 from 1.15.0 in 2.1 images

March 10, 2023

Upgraded Spark BigQuery connector version to 0.28.1 in 1.1 and 2.1 Dataproc Serverless for Spark runtimes.

March 06, 2023

Added stronger validations to disallow upper-case characters in template IDs per Resource Names guidance, which allows Workflow template creation to fail fast instead of failing at workflow template instantiation.

Added decision metric field in Stackdriver autoscaler logs.

March 02, 2023

Release Dataproc Serverless for Spark runtime 2.1 preview:

  • Spark 3.4.0-rc1
  • BigQuery Spark Connector 0.28.0
  • Cloud Storage Connector 2.2.11
  • Conda 22.11
  • Java 17
  • Python 3.10
  • R 4.2
  • Scala 2.13

February 28, 2023

--properties=dataproc:agent.ha.enabled=true can now be used to enable the Dataproc Agent in high availability mode. This property is supported by Dataproc Image versions 2.0 and above.

February 23, 2023

Upgrade Spark to 3.3.2 and its dependencies in 1.1 and 2.0 Dataproc Serverless for Spark runtimes:

  • Jackson to 2.13.5
  • Jetty to 9.4.50.v20221201
  • ORC to 1.8.2
  • Protobuf to 3.21.12
  • RoaringBitmap to 0.9.39

February 17, 2023

New sub-minor versions of Dataproc images:

  • 1.5.82-debian10, 1.5.82-rocky8, 1.5.82-ubuntu18
  • 2.0.56-debian10, 2.0.56-rocky8, 2.0.56-ubuntu18
  • 2.1.4-debian11, 2.1.4-rocky8, 2.1.4-ubuntu20

February 10, 2023

Dataproc Serverless for Spark now supports unconditional TTL to batches. The workload will be terminated after the TTL without waiting for work to complete.

Dataproc Serverless for Spark now supports statically-sized Dataproc Serverless for Spark batch workloads with more than 500 executors.

Add support for filters when listing batches. Batches may be filtered on one or more of batch_id, batch_uuid, state, or create_time (for example, state = RUNNING AND create_time < "2023-01-01T00:00:0Z"). See Filter expressions for more information.

Generate a warning when initialization actions are used in a cluster created with a driver node group.

The default Dataproc Serverless for Spark runtime version has changed to 2.0.

February 03, 2023

1.0.29 is the last release of the Dataproc Serverless for Spark runtime version 1.0, it will no longer be supported and will not receive new releases.

Upgrade Cloud Storage connector to 2.2.11 version in Dataproc Serverless for Spark runtimes.

January 27, 2023

Announcing the General Availability (GA) release of Dataproc Serverless for Spark runtime version 1.1, which includes the following components:

  • Spark 3.3.1
  • BigQuery Spark Connector 0.28.0
  • Cloud Storage Connector 2.2.9
  • Conda 22.11
  • Java 11
  • Python 3.10
  • R 4.2
  • Scala 2.12

Dataproc Serverless for Spark runtime version 1.0 changed to non-LTS because of the release of backward-compatible Dataproc Serverless for Spark runtime version 1.1 LTS.

January 24, 2023

January 23, 2023

New sub-minor versions of Dataproc images:

  • 1.5.80-debian10, 1.5.80-rocky8, 1.5.80-ubuntu18
  • 2.0.54-debian10, 2.0.54-rocky8, 2.0.54-ubuntu18
  • 2.1.2-debian11, 2.1.2-rocky8, 2.1.2-ubuntu20

Added support for enabling Hive Metastore OSS metrics by passing hivemetastore to --metric-sources property during cluster creation.

Added support for Dataproc Metastore integration with Trino.

Upgraded Parquet to 1.12.2 for 2.1 images.

The value of hive.server2.builtin.udf.blacklist is now set by default to reflect,reflect2 in hive-site.xml to prevent arbitrary code execution.

January 13, 2023

December 19, 2022

New sub-minor versions of Dataproc images:

  • 1.5.79-debian10, 1.5.79-rocky8, 1.5.79-ubuntu18
  • 2.0.53-debian10, 2.0.53-rocky8, 2.0.53-ubuntu18
  • 2.1.1-debian11, 2.1.1-rocky8, 2.1.1-ubuntu20

Backported Spark patch in Dataproc Serverless for Spark runtime 1.0 and 2.0:

  • SPARK-40481: Ignore stage fetch failure caused by decommissioned executor.

December 12, 2022

General Availability (GA) release of Dataproc 2.1 images.

New sub-minor versions of Dataproc images:

  • 1.5.78-debian10, 1.5.78-rocky8, 1.5.78-ubuntu18
  • 2.0.52-debian10, 2.0.52-rocky8, 2.0.52-ubuntu18
  • 2.1.0-debian11, 2.1.0-rocky8, 2.1.0-ubuntu20

Upgrade Cloud Storage connector version to 2.1.9 for 1.5 images.

Upgrade Cloud Storage connector version to 2.2.9 for 2.1 images.

Dataproc Serverless for Spark runtime 1.0:

  • Upgrade to Spark to 3.2.3
  • Upgrade Cloud Storage connector to 2.2.9
  • Upgrade Spark dependencies:
    • Jetty to 9.4.49.v20220914
    • ORC to 1.7.7
    • Protobuf to 3.19.6
    • RoaringBitmap to 0.9.35
    • Scala to 2.12.17

Dataproc Serverless for Spark runtime 2.0:

  • Upgrade Cloud Storage connector to 2.2.9
  • Upgrade Spark dependencies:
    • Protobuf to 3.21.9
    • RoaringBitmap to 0.9.35

Use jemalloc as a default OS memory allocator in Dataproc Serverless for Spark runtime.

Backport Spark patches in Dataproc Serverless for Spark runtime 1.0 and 2.0:

  • SPARK-39324: Log ExecutorDecommission as INFO level in TaskSchedulerImpl
  • SPARK-40168: Handle SparkException during shuffle block migration
  • SPARK-40269: Randomize the orders of peer in BlockManagerDecommissioner
  • SPARK-40778: Make HeartbeatReceiver as an IsolatedRpcEndpoint

December 09, 2022

Added the dataproc.googleapis.com/job/state metric to track the status of Dataproc Jobs states (such as, RUNNING or PENDING). This metric is collected by default and is not chargeable to customers.

Dataproc job IDs are now queryable and viewable from MQL(Monitoring Query Language), and the metric can be used for long-running job monitoring and alerting.

December 06, 2022

Dataproc Serverless for Spark runtime version 2.0 will become the default Dataproc Serverless for Spark runtime version on January 24, 2023 (instead of December 13, 2022, as previously announced).

November 17, 2022

Dataproc Serverless for Spark supports Spark and System metrics. These metrics are enabled by default. Spark driver and executor metrics can be customised using overrides.

Added support for Dataproc to attach to a gRPC Dataproc Metastore in any region.

Secure Boot, Virtual trusted platform module (vTPM), and Integrity monitoring Shielded VM features are enabled by default for Dataproc on Compute Engine clusters that use 2.1 preview images.

Nodemanagers in DECOMMISSIONING, NEW, and SHUTDOWN state are now included in the /cluster/yarn/nodemanagers metric.

Dataproc Serverless for Spark now shows the subminor runtime version used in the runtimeConfig.version field,

Fixed a bug that caused a Dataproc cluster with a Dataproc Metastore service to fail the creation process, if the cluster was in the same network but different subnetworks.

November 14, 2022

Dataproc Serverless for Spark now now uses runtime version 1.0.23 and 2.0.3.

New sub-minor versions of Dataproc images:

1.5.77-debian10, 1.5.77-rocky8, 1.5.77-ubuntu18,

2.0.51-debian10, 2.0.51-rocky8, 2.0.51-ubuntu18,

preview 2.1.0-RC4-debian11, preview 2.1.0-RC4-rocky8, preview 2.1.0-RC4-ubuntu20.

Downgraded google-auth-oauthlib Python package to fix gcsfs Python package for 2.0 and 2.1 images.

Backported HIVE-17317 in the latest 2.0 and 2.1 images.

Dataproc Serverless for Spark runtime version 1.0.23 and 2.0.3 downgrades google-auth-oauthlib Python package to fix gcsfs Python package.

Upgraded Apache Commons Text to 1.10.0 for Knox in 1.5 images, and for Spark, Pig, Knox in 2.0 images, addressing CVE-2022-42889.

Dataproc Serverless for Spark runtime version 1.0.23 and 2.0.3 adds PyMongo Python library.

November 11, 2022

Dataproc Serverless for Spark runtime versions 1.0.22 and 2.0.2 will be deprecated on 11/11/2022. New batch submissions that use these runtime versions will fail starting 11/11/2022. This is due to an update to the google auth library which breaks running Pyspark batch workloads having dependency on gcsfs. Upcoming runtime versions will address this issue.

Dataproc images 2.0.50 and preview 2.1.0-RC3 are deprecated and cluster creations based on these images will fail starting 11/11/2022. This is due to an update to the google auth library which breaks running Pyspark batch workloads having dependency on gcsfs. Upcoming image versions will have a fix to address this issue.

November 07, 2022

New sub-minor versions of Dataproc images:

1.5.76-debian10, 1.5.76-rocky8, 1.5.76-ubuntu18

2.0.50-debian10, 2.0.50-rocky8, 2.0.50-ubuntu18

preview 2.1.0-RC3-debian11, preview 2.1.0-RC3-rocky8, preview 2.1.0-RC3-ubuntu20,

Dataproc Serverless for Spark now now uses runtime version 1.0.22 and 2.0.2.

If a Dataproc Metastore service uses the gRPC endpoint protocol, a Dataproc or self-managed cluster located in any region can attach to the service.

October 31, 2022

Dataproc Serverless for Spark now allows the customization of driver and executor memory using the following properties:

  • spark.driver.memory
  • spark.driver.memoryOverhead
  • spark.executor.memory
  • spark.executor.memoryOverhead

Dataproc Serverless for Spark now outputs approximate_usage after a workload finishes that shows the approximate DCU and shuffle storage resource consumption by the workload.

Removed the Auto Zone placement check for supported machine types.

October 28, 2022

The following preview Dataproc image versions are available:

  • 2.1.0-RC2-debian11
  • 2.1.0-RC2-rocky8
  • 2.1.0-RC2-ubuntu20

The following component versions are available for use with the 2.1.0-RC2 images (the HBase and Druid components are not supported in 2.1 image versions):

  • Apache Atlas 2.2.0

  • Apache Flink 1.15.0

  • Apache Hadoop 3.3.3

  • Apache Hive 3.1.3

  • Apache Hive WebHCat 3.1.3

  • Apache Kafka 3.1.0

  • Apache Pig 0.18.0-SNAPSHOT

  • Apache Spark 3.3.0

  • Apache Sqoop v1 1.5.0-SNAPSHOT

  • Apache Sqoop v2 1.99.6

  • Apache Tez 0.10.1

  • Cloud Storage Connector hadoop3-2.2.8

  • Conscrypt 2.5.2

  • Docker 20.10

  • Hue 4.10.0

  • Java temurin-11-jdk

  • JupyterLab Notebook 3.4

  • Oozie 5.2.1

  • Presto 376

  • Python 3.10

  • R 4.1

  • Ranger 2.2.0

  • Scala 2.12.14

  • Solr 9.0.0

  • Zeppelin Notebook 0.10.1

  • Zookeeper 3.8.0

Dataproc Serverless for Spark now now uses runtime version 1.0.21 and 2.0.1.

Dataproc Serverless for Spark runtime version 2.0.1 upgrades Apache Commons Text to 1.10.0, addressing CVE-2022-42889

Dataproc Serverless for Spark runtime version 2.0.1 upgrades the following components:

October 26, 2022

All Dataproc Serverless for Spark runtime versions prior to 1.0.21 and 2.0.1 will be deprecated on November 2, 2022.

October 25, 2022

Dataproc Serverless for Spark runtime version 2.0 will become the default Dataproc Serverless for Spark runtime version on December 13, 2022.

October 24, 2022

Dataproc Serverless for Spark now supports spark.dataproc.diagnostics.enabled property that enables auto diagnostics on Batch failure. Note that enabling auto diagnostics will hold compute and storage quota after Batch is complete and until diagnostics is finished.

October 21, 2022

New sub-minor versions of Dataproc images:

1.5.75-debian10, 1.5.75-rocky8, 1.5.75-ubuntu18

2.0.49-debian10, 2.0.49-rocky8, 2.0.49-ubuntu18

Announcing the General Availability (GA) release of Dataproc Serverless for Spark runtime 2.0.

Dataproc Serverless for Spark now uses runtime version 1.0.20 and 2.0.0.

Upgraded Cloud Storage connector version to 2.2.8 in the latest 2.0 images.

Upgraded the Conscrypt library to 2.5.2 in the latest 1.5 and 2.0 images.

Dataproc Serverless for Spark runtime version 2.0.0 upgrades the following components:

  • Conda to 22.9
  • Jetty to 9.4.49.v20220914
  • ORC to 1.8.0
  • Protobuf to 3.21.7
  • RoaringBitmap to 0.9.32

Disabled auto deletion of files under /tmp in the latest Rocky images. Previous Rocky images have files in the /tmp folder deleted every 10 days due to default OS system setting in /usr/lib/tmpfiles.d/tmp.conf.

Changed Hive TokenStoreDelegationTokenSecretManager in the latest 1.5 and 2.0 images so that it updates the base class's current key ID after generating a new master key. This is important for users of DBTokenStore, which generates key IDs based on a monotonically increasing sequence from the database. Prior to this fix, there was a race condition during master key rollover that could cause it to attempt updating the prior master key using an incorrect ID value. This would fail and then quickly retry, sometimes multiple times, causing too many rows in the database.

Set yarn:spark.yarn.shuffle.stop_on_failure to true by default in the latest 1.5 and 2.0 images. This change causes YARN node manager startup to fail if the Spark external shuffle service startup fails. On VM boot, Dataproc will continuously restart the YARN node manager until it is able to start. This change reduces Spark executor errors, such as: org.apache.spark.SparkException: Unable to register with external shuffle server due to : Failed to connect to <worker host>:7337, particularly when starting a stopped cluster. See Spark external shuffle service documentation for details.

Backported the patch for HADOOP-18316 in the latest 2.0 images, addressing CVE-2022-25168.

Backported the patch for HIVE-25468 in the latest 1.5 and 2.0 images, addressing CVE-2021-34538.

Addressing CVE-2022-23305, CVE-2022-23302, CVE-2021-4104, CVE-2019-17571, migrated log4j 1.2 to reload4j for Hadoop, Spark in the latest 1.5 images and Hadoop, Spark, ZooKeeper, Oozie, Knox in the latest 2.0 images.

Enabled Spark authentication and encryption for Kerberos enabled clusters created with the latest 1.5 and 2.0 images.

Set HDFS /user/<name> directory permission with owner=<name> and mode=700 for Kerberos enabled clusters created with the latest 1.5 and 2.0 images.

Backported the patch for SPARK-36383 in the latest 2.0 images.

Backported the patch for HIVE-19310 in the latest 1.5 images.

Backported the patch for HIVE-20004 in the latest 2.0 images.

Fixed an issue in which Presto queries might fail when submitted to HA clusters in the latest 1.5 and 2.0 images.

Fixed a bug where metrics created based on the yarn:yarn.resourcemanager.metrics.runtime.buckets property were not exported to Cloud Monitoring, even though listed in --metric-overrides during cluster creation.

Fixed a "gsutil not found" issue in the latest 1.5 and 2.0 Ubuntu images.

Backported the patch for HIVE-26447 in the latest 2.0 images.

Backported the patch for HIVE-20607 in the latest 2.0 images.

October 05, 2022

Dataproc is now available in the me-west1 region (Tel Aviv, Israel).

October 03, 2022

Preemptible SPOT VMs can be used as secondary workers in a Dataproc cluster. Unlike legacy preemptible VMs with a 24-hour maximum lifetime, Spot VMs have no maximum lifetime.

October 01, 2022

Dataproc Serverless for Spark now supports Artifact Registry with image streaming.

Dataproc Metastore: Fixed an endpoint resolution issue that caused 500 type errors for valid setups. The service was overly aggressive in describing networks and subnetworks attached to the service via the NetworkConfig field.

September 27, 2022

Dataproc Auto Zone Placement now takes ANY reservation into account by default.

September 26, 2022

Dataproc Serverless for Spark now uses runtime version 1.0.19 and 2.0.0-RC4, which also upgrades both runtimes to Cloud Storage Connector to 2.2.8.

September 20, 2022

Dataproc Serverless for Spark: You can now use the spark.dynamicAllocation.executorAllocationRatio property to configure how aggressively to scale up Serverless workloads. A value of 1.0 provides maximum scale up.

Dataproc Serverless for Spark: Reduced the latency between batch workload completion and when a batch is marked SUCCEEDED.

Dataproc Serverless for Spark: Increased initial and maximum Spark executor limits to 500 and 2,000, respectively.

Dataproc Serverless for Spark: Sets a maximum limit of 500 workers per scale up or scale down operation.

Dataproc on Compute Engine: Stop all master and worker VMs when starting a cluster fails due to stockout or insufficient quota.

September 19, 2022

Dataproc Serverless for Spark now uses runtime version 1.0.18 and 2.0.0-RC3.

September 12, 2022

Dataproc Serverless for Spark now uses runtime version 1.0.17 and 2.0.0-RC2.

September 08, 2022

Avoid using the following image versions when creating new clusters:

  • 2.0.31-debian10, 2.0.31-ubuntu18, 2.0.31-rocky8
  • 2.0.32-debian10, 2.0.32-ubuntu18, 2.0.32-rocky8
  • 2.0.33-debian10, 2.0.33-ubuntu18, 2.0.33-rocky8
  • 1.5.57-debian10, 1.5.57-ubuntu18, 1.5.57-rocky8
  • 1.5.58-debian10, 1.5.58-ubuntu18, 1.5.58-rocky8
  • 1.5.59-debian10, 1.5.59-ubuntu18, 1.5.59-rocky8

If your cluster uses one of these image versions, there is a small chance that the cluster might enter an ERROR_DUE_TO_UPDATE state while being updated, either manually or as a result of autoscaling. If that happens, contact support. You can avoid future occurrences by creating new clusters with a newer image version.

September 01, 2022

Fixed issue where gcloud dataproc batches list hangs when a large number of batches is present.

August 24, 2022

Announcing the Preview release of Dataproc custom constraints, which can be used to allow or deny specific operations on Dataproc clusters.

August 22, 2022

Announcing Dataproc Serverless for Spark preview runtime version 2.0.0-RC1, which includes the following components:

  • Spark 3.3.0
  • Cloud Storage Connector 2.2.7
  • Java 17
  • Conda 4.13
  • Python 3.10
  • R 4.1
  • Scala 2.13

Dataproc Serverless for Spark now uses runtime version 1.0.16, which upgrades the following components to the following versions:

  • Spark 3.2.2
  • Avro 1.11.1
  • Hadoop 3.3.4
  • Jetty 9.4.48.v20220622
  • ORC 1.7.5
  • RoaringBitmap 0.9.31
  • Scala 2.12.16

August 13, 2022

New sub-minor versions of Dataproc images:

1.5.73-debian10, 1.5.73-rocky8, 1.5.73-ubuntu18

2.0.47-debian10, 2.0.47-rocky8, 2.0.47-ubuntu18

Enabled Spark authentication and encryption for Kerberos clusters in 1.5 and 2.0 images.

Dataproc Serverless for Spark now uses runtime version 1.0.15, which upgrades the following Spark dependencies to the following versions:

  • Jackson 2.13.3
  • Jetty 9.4.46.v20220331
  • ORC 1.7.4
  • Parquet 1.12.3
  • Protobuf 3.19.4
  • RoaringBitmap 0.9.28

Dataproc on Compute Engine images now have master VM memory protection enabled by default. Jobs may be terminated to prevent the master VM running out of memory.

FallbackHiveAuthorizerFactory is now set by default on newly created 1.5 and 2.0 image clusters that have the any of the following features enabled:

If you encounter a Cannot modify <PARAM> or similar runtime error when running a SET statement in a Hive query, this means the parameter is not in list of allowable runtime parameters. You can allow the parameter using hive.security.authorization.sqlstd.confwhitelist.append as a cluster property when you create a cluster.

Example: 

--properties="hive:hive.security.authorization.sqlstd.confwhitelist.append=tez.application.tags,<ADDITIONAL-1>,<ADDITIONAL-2>"

August 01, 2022

New sub-minor versions of Dataproc images:

1.5.72-debian10, 1.5.72-rocky8, 1.5.72-ubuntu18

2.0.46-debian10, 2.0.46-rocky8, 2.0.46-ubuntu18

Upgraded Hadoop to version 3.2.3 in 2.0 images.

Upgraded Hadoop to version 2.10.2 version 2.10.2 in 1.5 images.

Default MySQL instance root password changed to a random value in 1.5 and 2.0 images. New password is now stored in MySQL configuration file accessible only by the OS level root user.

Backported the patch for KNOX-1997 in 2.0 images.

Backported the patch for HIVE-19048 in 2.0 images.

Backported the patches for HIVE-19047 and HIVE-19048 in 1.5 images.

July 07, 2022

Dataproc support for the following images has been extended to the following dates:

July 01, 2022

New sub-minor versions of Dataproc images:

1.5.71-debian10, 1.5.71-rocky8, 1.5.71-ubuntu18

2.0.45-debian10, 2.0.45-rocky8, 2.0.45-ubuntu18

For 1.5 images and the 2.0.45-ubuntu18 image, backported the upstream fix for KNOX-1997.

June 21, 2022

New sub-minor versions of Dataproc images:

1.5.70-debian10, 1.5.70-rocky8, 1.5.70-ubuntu18

2.0.44-debian10, 2.0.44-rocky8, 2.0.44-ubuntu18

Dataproc Metastore: For 1.5 images, added a spark.hadoop.hive.eager.fetch.functions.enabled Spark Hive client property to control whether the client fetches all functions from Hive Metastore during initialization. The default setting is true, which preserves the existing behavior of fetching all functions. If set to false, the client will not fetch all functions during initialization, which can help reduce high latency during initialization, particularly when there are many functions and the Metastore is not located in the client's region.

For 1.5 and 2.0 images, backported YARN-9608 to fix the issue in graceful decommissioning.

June 14, 2022

Announcing the General Availability (GA) release of Dataproc Custom OSS Metrics GA, which collects then integrates Dataproc cluster OSS component metrics into Cloud Monitoring.

New sub-minor versions of Dataproc images:

1.5.69-debian10, 1.5.69-rocky8, 1.5.69-ubuntu18

2.0.43-debian10, 2.0.43-rocky8, 2.0.43-ubuntu18

Backported the patch for HBASE-23287 to HBase 1.5.0 in 1.5 image

June 13, 2022

Announcing the General Availability (GA) release of Ranger Cloud Storage plugin. This plugin activates an authorization service on each Dataproc cluster VM, which evaluates requests from the Cloud Storage connector against Ranger policies and, if the request is allowed, returns an access token for the cluster VM service account

Dataproc is now available in the us-south1 region (Dallas, Texas).

June 06, 2022

Announcing the General Availability (GA) release of Dataproc Persistent History Server, which provides web interfaces to view job history for jobs run on active or deleted Dataproc clusters.

Dataproc Serverless for Spark now uses runtime version 1.0.13.

New sub-minor versions of Dataproc images:

1.5.68-debian10, 1.5.68-rocky8, 1.5.68-ubuntu18

2.0.42-debian10, 2.0.42-rocky8, 2.0.42-ubuntu18

Dataproc Serverless for Spark runtime versions 1.0.2, 1.0.3 and 1.0.4 are unavailable for new batch submissions.

Dataproc on GKE Spark 3.1 images upgraded to Spark version 3.1.3.

Upgrade Cloud Storage connector version 2.1.8 for 1.5 images only.

Fixed a bug where HDFS directories initialization could fail when user names in a project contain special characters.

Fix a Dataproc on GKE bug that caused upload of driver logs to Cloud Storage to fail.

June 01, 2022

Dataproc is now available in the us-east5 region (Columbus, Ohio).

May 31, 2022

Dataproc is now available in the europe-southwest1 region (Madrid, Spain).

Dataproc is now available in the europe-west9 region (Paris, France).

May 30, 2022

New sub-minor versions of Dataproc images:

1.5.67-debian10, 1.5.67-ubuntu18, 1.5.67-rocky8

2.0.41-debian10, 2.0.41-ubuntu18, 2.0.41-rocky8

Dataproc on GKE error messages now provide additional information.

Backported fixes for HIVE-22098, HIVE-23809, HIVE-20462, HIVE-21675 to Hive 3.1 in Dataproc 2.0 images.

Fix a bug where properties related to Kerberos cross realm trust were not properly set.

Fixed a bug where older-image (for example, 1.3.95) cluster create operations failed with the error message : "does not support specifying local SSD interface other than 'SCSI'".

May 23, 2022

New sub-minor versions of Dataproc images:

1.5.66-debian10, 1.5.66-ubuntu18, 1.5.66-rocky8

2.0.40-debian10, 2.0.40-ubuntu18, 2.0.40-rocky8

Upgraded Spark to 3.1.3 in Dataproc image version 2.0.

Fixed a bug where job was not being marked as terminated after master node reboot.

Fixed a bug where Flink was not able to run on HA clusters.

Backported the fix for HIVE-20514 to Hive 2.3 in Dataproc image version 1.5.

Fixed a bug with HDFS directories initialization when core:fs.defaultFS is set to an external HDFS.

May 09, 2022

New sub-minor versions of Dataproc images:

1.5.65-debian10, 1.5.65-ubuntu18, 1.5.65-rocky8

2.0.39-debian10, 2.0.39-ubuntu18, 2.0.39-rocky8

Dataproc Serverless for Spark now uses runtime version 1.0.12.

Fixed an issue where chronyd systemd service failed to start due to a race condition between systemd-timesyncd and chronyd.

Dataproc Serverless for Spark runtime version 1.0.1 is unavailable for new batch submissions.

May 03, 2022

New sub-minor versions of Dataproc images:

1.5.64-debian10, 1.5.64-ubuntu18, 1.5.64-rocky8

2.0.38-debian10, 2.0.38-ubuntu18, 2.0.38-rocky8

Dataproc Serverless for Spark now uses runtime version 1.0.11.

If you request to cancel a job in one of the following states, Dataproc will return the job, but not initiate cancellation, since it is already in progress: CANCEL_PENDING, CANCEL_STARTED, or CANCELLED.

When submitting a Dataproc job or workflow that selects a cluster that matches the specified labels, Dataproc will avoid choosing clusters that are in a state that disallows running jobs. Specifically, Dataproc will only choose among clusters in one of the following states: RUNNING, UPDATING, CREATING, or ERROR_DUE_TO_UPDATE.

Added Dataproc Serverless support for updating the Cloud Storage connector using the dataproc.gcsConnector.version and dataproc.gcsConnector.uri properties.

Hive: Upgrade to Apache ORC 1.5.13 in image version 2.0. Notable in this release are 2 bug fixes: ORC-598 and ORC-672, related to handling ORC files with arrays larger than 1024 elements.

Dataproc correctly defaults NodePool locations when the GKE cluster is in us-east1 and europe-west1.

Dataproc Serverless for Spark runtime version 1.0.0 is unavailable for new batch submissions.

April 22, 2022

New sub-minor versions of Dataproc images:

1.5.63-debian10, 1.5.63-ubuntu18, 1.5.63-rocky8

2.0.37-debian10, 2.0.37-ubuntu18, 2.0.37-rocky8

Dataproc Serverless for Spark now uses runtime version 1.0.10.

Cloud Storage connector version upgraded to 2.2.6 in image version 2.0.

Hive: Bundle threeten classes in hive-exec.jar in image version 2.0. ORC now requires date handling classes in the org.threeten package, which are not present in hive-exec.jar at query time.

HIVE-22589 fixed this bug upstream, but it was part of a large new feature. Instead, this change applies a small targeted fix to address the bug.

April 20, 2022

Dataproc is now available in the europe-west8 region (Milan, Italy).

April 13, 2022

Announcing the General Availability (GA) release of Dataproc on GKE, which allows you to execute Big Data applications using the Dataproc jobs API on GKE clusters.

April 11, 2022

The dataproc:dataproc.performance.metrics.listener.enabled cluster property, which is enabled by default, listens on port 8791 on all master nodes to extract performance-related telemetry Spark metrics. The metrics are published to the Dataproc service for it to use to set better defaults and improve the service. To opt-out of this feature, set dataproc:dataproc.performance.metrics.listener.enabled=false when creating a Dataproc cluster.

New sub-minor versions of Dataproc images:

1.5.62-debian10, 1.5.62-ubuntu18, and 1.5.62-rocky8

2.0.36-debian10, 2.0.36-ubuntu18, and 2.0.36-rocky8

Changed the owner of /usr/lib/knox/conf/gateway-site.xml from root:root to knox:knox.

Fixed and issue in which the Dataproc autoscaler would sometimes try to scale down a cluster by more than one thousand secondary worker nodes at one time. Now, the autoscaler will scale down at most one thousand nodes at one time. In cases where the autoscaler previously would have scaled down more than one thousand nodes at one time, it will scale down the nodes by at most one thousand nodes, and a log will be written to the autoscaler log noting this occurrence.

Fixed bugs that could cause Dataproc to delay marking a job cancelled.

April 01, 2022

New sub-minor versions of Dataproc images:

1.5.61-debian10, 1.5.61-ubuntu18, and 1.5.61-rocky8

2.0.35-debian10, 2.0.35-ubuntu18, and 2.0.35-rocky8

Changed the owner of /var/lib/zookeeper/myid from root to zookeeper.

March 25, 2022

New sub-minor versions of Dataproc images:

1.5.60-debian10, 1.5.60-ubuntu18, and 1.5.60-rocky8

2.0.34-debian10, 2.0.34-ubuntu18, and 2.0.34-rocky8

March 17, 2022

New sub-minor versions of Dataproc images:

1.5.59-debian10, 1.5.59-ubuntu18, and 1.5.59-rocky8

2.0.33-debian10, 2.0.33-ubuntu18, and 2.0.33-rocky8

March 07, 2022

New sub-minor versions of Dataproc images:

1.5.58-debian10, 1.5.58-ubuntu18, and 1.5.58-rocky8

2.0.32-debian10, 2.0.32-ubuntu18, and 2.0.32-rocky8

Fixed bug where clusters created via Dataproc Hub failed with Unit file jupyter.service does not exist error.

Fixed bug where clusters created with Kerberos failed with SSL Certificate string is too long error.

February 18, 2022

Added support for Enhanced Flexibility Mode (EFM) with primary worker shuffle mode on Spark for image version 2.0.

General Availability (GA) release of new Rocky Linux based images: 1.5.57-rocky8 and 2.0.31-rocky8. These images are replacing CentOS images which are EOL.

Dataproc Serverless for Spark now uses runtime version 1.0.4, which updates GCS connector to 2.2.5 version.

New sub-minor versions of Dataproc images:

1.5.57-debian10, 1.5.57-ubuntu18, and 1.5.57-rocky8

2.0.31-debian10, 2.0.31-ubuntu18, and 2.0.31-rocky8

Upgraded Cloud Storage connector version to 2.2.5 in image version 2.0.

Upgraded Cloud Storage connector version to 2.1.7 in image version 1.5.

CentOS images are EOL. 1.5.56-centos8 and 2.0.30-centos8 are the final CentOS based images. CentOS images are no longer supported and will not receive new releases.

February 17, 2022

A script that checks if a project or organization is using an unsupported Dataproc image is available for downloading (see Unsupported Dataproc versions).

February 15, 2022

Dataproc images prior to 1.3.95, 1.4.77, 1.5.53, and 2.0.27 are deprecated and cluster creations based on these images will fail starting 2/28/2022.

February 11, 2022

February 07, 2022

Added cluster_type field to job and operation metrics in Cloud Monitoring.

February 01, 2022

Enabled the Resource Manager UI and HA capable UIs in HA cluster mode.

1.4.80-debian10 and 1.4.80-ubuntu18 are the last releases for the 1.4 images. Dataproc 1.4 images will no longer be supported and will not receive new releases.

New sub-minor versions of Dataproc images:

1.4.80-debian10 and 1.4.80-ubuntu18

1.5.56-debian10, 1.5.56-ubuntu18, and 1.5.56-centos8

2.0.30-debian10, 2.0.30-ubuntu18, and 2.0.30-centos8

Configured Zeppelin Spark interpreter to run in YARN client mode by default for image version 2.0.

January 31, 2022

Dataproc Serverless for Spark now uses runtime version 1.0.2, which updates Spark to 3.2.1 version.

January 24, 2022

Dataproc Serverless for Spark now uses runtime version 1.0.1, which includes improved error messaging for network connectivity issues.

January 19, 2022

Announcing the General Availability (GA) release of Dataproc Serverless for Spark, which allows you to run your Spark jobs on Dataproc without having to spin up and manage your own cluster.

January 18, 2022

Added support for Dataproc Metastore's beta NetworkConfig field. Beta services using this field can now be used in conjunction with v1 Dataproc clusters.

Dataproc extracts the warehouse directory from the Dataproc Metastore service for the cluster-local warehouse directory.

January 17, 2022

New sub-minor versions of Dataproc images:

1.4.79-debian10 and 1.4.79-ubuntu18

1.5.55-debian10, 1.5.55-ubuntu18, and 1.5.55-centos8

2.0.29-debian10, 2.0.29-ubuntu18, and 2.0.29-centos8

Dataproc images 1.4.79, 1.5.55, and 2.0.29, listed above, were updated with log4j version 2.17.1. It is strongly recommended that your clusters use previously released images 1.4.77, 1.5.53, or 2.0.27, or higher (see Supported Dataproc versions). While not urgent nor strongly recommended, Dataproc advises you to create or recreate Dataproc clusters with the latest sub-minor image versions when possible.

The Cloud Storage connector jar is installed on the Solr server (even if dataproc:solr.gcs.path property is not set). Applies to image versions 1.4, 1.5, and 2.0.

Migrated to Eclipse Temurin JDK in image versions 1.4, 1.5, and 2.0.

Fixed a bug where cluster restart disabled Solr and Ranger services even if the components are selected. Applies to image versions 1.4, 1.5, and 2.0.

YARN-8865: RMStateStore contains large number of expired RMDelegationToken. Applies to 1.5 images.

RANGER-3324: Make optimized db schema script idempotent for MySQL DB. Applies to 2.0 images.

January 09, 2022

New sub-minor versions of Dataproc images:

1.4.78-debian10, and 1.4.78-ubuntu18

1.5.54-centos8, 1.5.54-debian10, and 1.5.54-ubuntu18

2.0.28-centos8, 2.0.28-debian10, and 2.0.28-ubuntu18

Dataproc images 1.4.78, 1.5.54, and 2.0.28, listed above, were updated with log4j version 2.17.0. It is strongly recommended that your clusters use previously released images 1.4.77, 1.5.53, or 2.0.27, or higher (see Supported Dataproc versions). While not urgent nor strongly recommended, Dataproc advises you to create or recreate Dataproc clusters with the latest sub-minor image versions when possible.

Upgraded Cloud Storage connector version to 2.2.4 in image version 2.0.

Fixed the problem that jars added with the --jars flag in gcloud dataproc jobs submit spark-sql are missing at runtime.

December 21, 2021

Dataproc has released 1.3.95-debian10/-ubuntu18 images with a one-time patch that addresses the Apache Log4j 2 CVE-2021-44228 and CVE-2021-45046 vulnerabilities, but note that that all 1.3 images remain unsupported, and Dataproc will not provide upgrades to 1.3 images .

December 18, 2021

Dataproc has released the following sub-minor image versions to address an Apache Log4j 2 vulnerability (also see Create a cluster and Recreate and update a cluster for more information). Note: These images supersede the 1.5 and 2.0 images listed in the December 16, 2021 release note:

1.5.53-centos8, 1.5.53-debian10, 1.5.53-ubuntu18,

2.0.27-centos8, 2.0.27-debian10, 2.0.27-ubuntu18

Removed the Geode interpreter from Zeppelin notebook, which is affected by https://nvd.nist.gov/vuln/detail/CVE-2021-45046.

December 16, 2021

Dataproc has released the following [sub-minor image versions](https://cloud.google.com/dataproc/docs/concepts/versioning/dataproc-versions:

1.4.77-debian10, 1.4.77-ubuntu18,

1.5.52-centos8, 1.5.52-debian10, 1.5.52-ubuntu18,

2.0.26-centos8, 2.0.26-debian10, 2.0.26-ubuntu18

Upgraded log4j version to 2.16.0, which fixes https://nvd.nist.gov/vuln/detail/CVE-2021-44228.

December 13, 2021

Dataproc has added new images, listed in this release note, to address an Apache Log4j 2 vulnerability.

Note: these images have been superseded. by the 12/16/21 images (see the December 16, 2021 release note). Also see Create a cluster and Recreate and update a cluster for more information.

New sub-minor versions of Dataproc images:

1.4.76-debian10, 1.4.76-ubuntu18,

1.5.51-centos8, 1.5.51-debian10, 1.5.51-ubuntu18,

2.0.25-centos8, 2.0.25-debian10, 2.0.25-ubuntu18

Upgraded log4j version to 2.15.0, which fixes https://nvd.nist.gov/vuln/detail/CVE-2021-45046.

HIVE-21040: msck does unnecessary file listing at last level of directory tree. Applies to 1.5 and 2.0 images.

Fixed executor log links on Spark History Server Web UI for running and completed applications. Applies to 1.4 and 1.5 images.

Fixed a bug where driver log links on PHS Web UI stop working once the job cluster is deleted. Applies to 1.4 and 1.5 images.

YARN-8990: Fixed a Fairscheduler race condition. Applies to 2.0 images.

SPARK-7768: Make user-defined type (UDT) API public. Applies to 2.0 images.

SPARK-35817: Queries against wide Avro tables can be slow. Applies to 2.0 images.

November 17, 2021

Dataproc is now available in the southamerica-west1 region (Santiago, Chile).

November 01, 2021

Added the following new Apache Spark properties to control Cloud Storage flush behavior for event logs for 1.4 and later images:

  • spark.history.fs.gs.outputstream.type (default: BASIC)
  • spark.history.fs.gs.outputstream.sync.min.interval.ms (default: 5000ms).

Note: The default configuration of these properties enables the display of running jobs in the Spark History Server UI for clusters using Cloud Storage to store spark event logs.

Added support in 1.5 and 2.0 images to filter Spark Applications on the Spark History Server Web UI based on Cloud Storage path. Filtering is accomplished using the eventLogDirFilter parameter, which accepts any Cloud Storage path substring and will return applications that match the Cloud Storage path.

New sub-minor versions of Dataproc images:

1.4.75-debian10, 1.4.75-ubuntu18,

1.5.50-centos8, 1.5.50-debian10, 1.5.50-ubuntu18,

2.0.24-centos8, 2.0.24-debian10, 2.0.24-ubuntu18

Removed Apache Iceberg and Delta Lake libraries in 2.0 images because they are not compatible with Spark 3.1.

Upgraded Cloud Storage connector to version 2.2.3 on 2.0 Images.

The previous Dataproc on GKE beta documentation has been replaced with a Dataproc on GKE private preview sign up form. Existing beta customers can continue using the beta release, but note that the beta release is planned to be deprecated and removed.

Patched Hive in 2.0 images with HIVE-20187, which fixes a bug where Hive returned incorrect query results when hive.convert.join.bucket.mapjoin.tez is set to true.

Backported SPARK-31946 in 2.0 images.

Backported SPARK-23182 in 1.4 and 1.5 images. This prevents long-running Spark shuffle servers from leaking connections when they are not cleanly terminated.

Fixed stdout and stderr links in the Spark History Server Web UI in 2.0 images.

October 22, 2021

The dataproc:dataproc.cluster-ttl.consider-yarn-activity cluster property is now set to true by default for image versions 1.4.64+, 1.5.39+, and 2.0.13+. With this change, with clusters created with these image versions, Dataproc Cluster Scheduled Deletion by default will consider YARN activity, in addition to Dataproc Jobs API activity, when determining cluster idle time . This change does not affect clusters with images with lower version numbers: cluster idle time for those clusters will continue to be computed based on Dataproc Jobs API activity only. When using image versions 1.4.64+, 1.5.39+, and 2.0.13+, you can opt out of this changed behavior by setting this property to false when you create the cluster.

October 08, 2021

In a future announcement (on approximately October 22, 2021), Dataproc will announce that Cluster Scheduled Deletion by default will consider YARN activity, in addition to Dataproc Jobs API activity, when determining cluster idle time. This change will affect image versions 1.4.64+, 1.5.39+, and 2.0.13+. To test this feature now, create a cluster with a recent image, setting the dataproc:dataproc.cluster-ttl.consider-yarn-activity cluster property to true. Note: After this behavior becomes the default, you can opt out when you create a cluster by setting the property to false.

October 01, 2021

New sub-minor versions of Dataproc images:

1.4.73-debian10, 1.4.73-ubuntu18,

1.5.48-centos8, 1.5.48-debian10, 1.5.48-ubuntu18,

2.0.22-centos8, 2.0.22-debian10, 2.0.22-ubuntu18

Fixed an issue where complete YARN container logs were not visible in 1.5 and 2.0 Images.

HADOOP-15129: Fixed in 2.0 Images: Datanode cached namenode DNS lookup failure and could not startup on.

September 17, 2021

Updated August 19, 2021 release notes with cluster creation Failure Action feature.

September 13, 2021

New sub-minor versions of Dataproc images: 1.4.71-debian10, 1.4.71-ubuntu18, 1.5.46-centos8, 1.5.46-debian10, 1.5.46-ubuntu18, 2.0.20-centos8, 2.0.20-debian10, 2.0.20-ubuntu18

Added support for enabling/disabling Ubuntu Snap daemon with cluster property dataproc:dataproc.snap.enabled. The default value is "true". If set to "false", pre-installed Snap packages in the image won't be affected, but auto refresh will be disabled. Applies to all Ubuntu images.

HIVE-21018: Grouping/distinct on more than 64 columns should be possible. Applies to 2.0 images.

September 08, 2021

The following previously released sub-minor versions of Dataproc images included a bug where the dataproc user account was broken. This prevented some Dataproc services from functioning properly, which resulted in features being unavailable. In particular, this prevented Jupyter from running in clusters with Personal Cluster Authentication enabled.

These sub-minor versions have been rolled back, and can only be used when updating existing clusters that already use them:

  • 1.4.66-debian10, 1.4.66-ubuntu18
  • 1.4.67-debian10, 1.4.67-ubuntu18
  • 1.5.41-centos8, 1.5.41-debian10, 1.5.41-ubuntu18
  • 1.5.42-centos8, 1.5.42-debian10, 1.5.42-ubuntu18
  • 2.0.15-centos8, 2.0.15-debian10, 2.0.15-ubuntu18
  • 2.0.16-centos8, 2.0.16-debian10, 2.0.16-ubuntu18

September 07, 2021

Added additional messages to the error messages for networking and IAM errors when creating a new cluster.

August 30, 2021

New sub-minor versions of Dataproc images: 1.4.70-debian10, 1.4.70-ubuntu18, 1.5.45-centos8, 1.5.45-debian10, 1.5.45-ubuntu18, 2.0.19-centos8, 2.0.19-debian10, 2.0.19-ubuntu18

Backported SPARK-34295: Added a new spark.yarn.kerberos.renewal.excludeHadoopFileSystemsconfiguration option.

Image 2.0:

OOZIE-3599: Upgraded Jetty version to 9.4.

August 23, 2021

New sub-minor versions of Dataproc images: 1.4.69-debian10, 1.4.69-ubuntu18, 1.5.44-centos8, 1.5.44-debian10, 1.5.44-ubuntu18, 2.0.18-centos8, 2.0.18-debian10, and 2.0.18-ubuntu18.

Configured YARN ResourceManager to use port 8554 and Druid to use port 17071 for JMX Remote RMI port.

August 19, 2021

Added support for Dataproc Metastore in three recently turned up regions: .europe-west1, northamerica-northeast1, and asia-southeast1.

Users can now help assure the successful creation of a cluster by automatically deleting any failed primary workers (the master(s) and at least two primary workers must be successfully provisioned for cluster creation to succeed). To delete any failed primary workers when you create a cluster:

  1. Using gcloud: Set the gcloud dataproc clusters create --action-on-failed-primary-workers flag to "DELETE".

  2. Using the Dataproc clusters.create API: Set the actionOnFailedPrimaryWorkers field to "DELETE".

Dataproc issues a warning message if the staging or test bucket name contains an underscore.

August 13, 2021

New sub-minor versions of Dataproc images: 1.4.68-debian10, 1.4.68-ubuntu18, 1.5.43-centos8, 1.5.43-debian10, 1.5.43-ubuntu18, 2.0.17-centos8, 2.0.17-debian10, and 2.0.17-ubuntu18.

Upgrade Flink to version 1.12.5 in image 2.0.

HIVE-2527: Fixed slow Hive partition deletion for Cloud Object Stores with expensive ListFiles.

Fixed Jupyter startup on Personal Auth clusters on all images.

August 09, 2021

New sub-minor versions of Dataproc images: 1.4.67-debian10, 1.4.67-ubuntu18, 1.5.42-centos8, 1.5.42-debian10, 1.5.42-ubuntu18, 2.0.16-centos8, 2.0.16-debian10, and 2.0.16-ubuntu18.

SPARK-28290: Fixed an issue where Spark History Server failed to serve because of a wild card certificate in the 1.4 and 1.5 images.

August 03, 2021

Dataproc is now available in the northamerica-northeast2 region (Toronto).

August 02, 2021

1.3 images are no longer supported and will not receive new releases.

New sub-minor versions of Dataproc images: 1.4.66-debian10, 1.4.66-ubuntu18, 1.5.41-centos8, 1.5.41-debian10, 1.5.41-ubuntu18, 2.0.15-centos8, 2.0.15-debian10, and 2.0.15-ubuntu18.

In image 2.0, set the mapreduce.fileoutputcommitter.algorithm.version=2 property in Spark. This makes Spark commit algorithm version consistent with prior Dataproc image versions.

July 27, 2021

New sub-minor versions of Dataproc images: 1.3.94-debian10, 1.3.94-ubuntu18, 1.4.65-debian10, 1.4.65-ubuntu18, 1.5.40-centos8, 1.5.40-debian10, 1.5.40-ubuntu18, 2.0.14-centos8, 2.0.14-debian10, and 2.0.14-ubuntu18.

The following component versions were updated in image 2.0:

Fixed a rare bug that sometimes happened when scaling down the number of secondary workers in a cluster in which the update operation would fail with error 'Resource is not a member of' or 'Cannot delete instance that was already deleted'.

July 20, 2021

New sub-minor versions of Dataproc images: 1.3.93-debian10, 1.3.93-ubuntu18, 1.4.64-debian10, 1.4.64-ubuntu18, 1.5.39-centos8, 1.5.39-debian10, 1.5.39-ubuntu18, 2.0.13-centos8, 2.0.13-debian10, and 2.0.13-ubuntu18.

Upgraded Cloud Storage connector to version 2.2.2 on 2.0 images.

Fixed Hue installation on Ubuntu 2.0 images.

Fixed an issue on 1.4 and 1.5 images where temporary shuffle data could be leaked when running Enhanced Flexibility Mode (EFM) with Spark.

July 12, 2021

For 2.0+ image clusters, the dataproc:dataproc.master.custom.init.actions.mode cluster property can be set to RUN_AFTER_SERVICES to run initialization actions on the master after HDFS and any services that depend on HDFS are initialized. Examples of HDFS-dependent services include: HBase, Hive Server2, Ranger, Solr, and the Spark and MapReduce history servers. Default: RUN_BEFORE_SERVICES.

July 09, 2021

Custom image limitation: New images announced in the Dataproc release notes are not available for use as the base for custom images until one week from their announcement date.

The Dataproc v1beta2 APIs are deprecated. Please use the Dataproc v1 APIs.

July 07, 2021

The end date of support for Dataproc image version 1.4 has been extended from August, 2021 to November, 2021.

July 05, 2021

New sub-minor versions of Dataproc images: 1.3.92-debian10, 1.3.92-ubuntu18, 1.4.63-debian10, 1.4.63-ubuntu18, 1.5.38-centos8, 1.5.38-debian10, 1.5.38-ubuntu18, 2.0.12-centos8, 2.0.12-debian10, and 2.0.12-ubuntu18.

Upgraded Spark version to 2.4.8 in the following images:

  • Image 1.4
  • Image 1.5

Upgrade HBase to version 2.2.7 in image 2.0.

Minimum boot disk sizes for Dataproc images:

  • Image 2.0: 30GB
  • Image 1.5: 20GB
  • Image 1.4: 15GB
  • Image 1.3: 15GB

Fixed stdout/stderr links on Spark History Server Web UI of the Persistent History Server in the following images:

  • Image 1.4
  • Image 1.5

Fixed a bug where personal auth credentials would not propagate to every VM in the cluster if VPC service controls were enabled.

June 29, 2021

Dataproc is now available in the asia-south2 region (Delhi).

The following previously released sub-minor versions of Dataproc images have been rolled back and can only be used when updating existing clusters that already use them:

  • 1.3.91-debian10, 1.3.91-ubuntu18
  • 1.4.62-debian10, 1.4.62-ubuntu18
  • 1.5.37-centos8, 1.5.37-debian10, 1.5.37-ubuntu18
  • 2.0.11-centos8, 2.0.11-debian10, and 2.0.11-ubuntu18.

Added support for Dataproc Metastore in three new recently turned up regions: europe-west3, us-west1, and us-east1.

Introduced a new ERROR_DUE_TO_UPDATE state, which indicates a cluster has encountered an irrecoverable error while scaling. Clusters in this state cannot be scaled, but can accept jobs.

Fixed an issue where a spurious unrecognized property warning was generated when the dataproc:jupyter.listen.all.interfaces cluster property is set.

June 21, 2021

Dataproc is now available in the australia-southeast2 region (Melbourne).

June 18, 2021

Dataproc Component Gateway URLs for any two new clusters that have the same project ID, region, and name will be identical unless Dataproc Personal Cluster Authentication is enabled.

June 08, 2021

Custom image limitation: Currently, the following Dataproc image versions are the latest images that can be used as the base for custom images:

  • 1.3.89-debian10, 1.3.89-ubuntu18
  • 1.4.60-debian10, 1.4.60-ubuntu18
  • 1.5.35-debian10, 1.5.35-ubuntu18, 1.5.35-centos8
  • 2.0.9-debian10, 2.0.9-ubuntu18, 2.0.11-centos8

June 01, 2021

New sub-minor versions of Dataproc images: 1.3.91-debian10, 1.3.91-ubuntu18, 1.4.62-debian10, 1.4.62-ubuntu18, 1.5.37-centos8, 1.5.37-debian10, 1.5.37-ubuntu18, 2.0.11-centos8, 2.0.11-debian10, and 2.0.11-ubuntu18.

Image 1.3 - 2.0

  • All jobs now share a single JobthreadPool.

  • The number of Job threads in the Agent is configurable with the dataproc:agent.process.threads.job.min and dataproc:agent.process.threads.job.max cluster properties, defaulting to 10 and 100, respectively. The previous behavior was to always use 10 Job threads.

Image 2.0

  • Added snappy-jar dependency to Hadoop.
  • Upgraded versions of Python packages: nbdime 2.1 -> 3.0, pyarrow 2.0 -> 3.0, spyder 4.2 -> 5.0, spyder-kernels 1.10 -> 2.0, regex 2020.11 -> 2021.4.

Image 1.5 and 2.0

Image 1.3 - 2.0

  • SPARK-35227: Replace Bintray with the new repository service for the spark-packages resolver in SparkSubmit.

Image 2.0

  • Fixed the problem that the environment variable PATH was not set in YARN containers.

  • SPARK-34731: ConcurrentModificationException in EventLoggingListener when redacting properties.

May 20, 2021

You can customize the Conda environment during cluster creation using new Conda-related cluster properties. See Using Conda-related cluster properties.

Added validation for clusters created with Dataproc Metastore services to determine compatibility between the Dataproc image's Hive version and the DPMS service's hive version

April 23, 2021

Announcing Dataproc Confidential Compute: Dataproc clusters now support Compute Engine Confidential VMs.

New sub-minor versions of Dataproc images: 1.3.89-debian10, 1.3.89-ubuntu18, 1.4.60-debian10, 1.4.60-ubuntu18, 1.5.35-centos8, 1.5.35-debian10, 1.5.35-ubuntu18, 2.0.9-centos8, 2.0.9-debian10, and 2.0.9-ubuntu18.

Image 1.4

Image 1.5

  • CentOS only: adoptopenjdk is set as the default Java environment.

Image 1.5 and 2.0

  • Updated Oozie version to 5.2.1
  • The Jupyter optional component now uses the "GCS" subdirectory as the initial working directory when you open the JupyterLab UI.

April 16, 2021

Added the ability to stop and start high-availability clusters.

Fixed a bug where scale-down update cluster requests failed due to quota validation if the user project was over a quota limit.

April 05, 2021

Image 2.0:

March 31, 2021

Dataproc support of Dataproc Metastore services is now available in GA.

March 26, 2021

Image 2.0:

  • Changed default private IPv6 Google APIs access for 2.0 clusters from OUTBOUND to INHERIT_FROM_SUBNETWORK.

March 24, 2021

Dataproc is now available in the europe-central2 region (Warsaw).

March 23, 2021

The default Dataproc image is now image version 2.0.

New sub-minor versions of Dataproc images: 1.3.88-debian10, 1.3.88-ubuntu18, 1.4.59-debian10, 1.4.59-ubuntu18, 1.5.34-centos8, 1.5.34-debian10, 1.5.34-ubuntu18, 2.0.7-centos8, 2.0.7-debian10, and 2.0.7-ubuntu18.

Image 2.0:

  • Updated Iceberg to version 0.11.0.
  • Updated Flink to version 1.12.2.

Image 2.0:

  • HIVE-22373: File Merge tasks fail when containers are reused.

Fixed a bug that caused Hive jobs to fail on Ranger-enabled clusters.

The end date of support for Dataproc image version 1.3 has been extended from March, 2021 to July, 2021.

Fixed a bug where Spark event logs directory and history server directory could not be set to Cloud Storage correctly.

Fixed a bug where Presto property value with ';' could not be set correctly in the config file.

CVE-2020-13957: SOLR-14663: ConfigSets CREATE does not set trusted flag.

CVE-2020-1926: HIVE-22708: Test fix for http transport.

March 16, 2021

New sub-minor versions of Dataproc images: 1.3.87-debian10, 1.3.87-ubuntu18, 1.4.58-debian10, 1.4.58-ubuntu18, 1.5.33-centos8, 1.5.33-debian10, 1.5.33-ubuntu18, 2.0.6-centos8, 2.0.6-debian10, and 2.0.6-ubuntu18.

Image 2.0: Upgraded Spark to version 3.1.1

March 08, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 1 week on March 15, 2021.

March 05, 2021

New sub-minor versions of Dataproc images: 1.3.86-debian10, 1.3.86-ubuntu18, 1.4.57-debian10, 1.4.57-ubuntu18, 1.5.32-centos8, 1.5.32-debian10, 1.5.32-ubuntu18, 2.0.5-debian10, and 2.0.5-ubuntu18

Image 2.0:

Fixed a bug where YARN applications launched by Hive jobs were not correctly tagged, leading to missing YARN application status from job state.

Fixed the permission for mounted SSD Hadoop directories.

March 02, 2021

Added the --cluster-labels flag to gcloud dataproc jobs submit to allow submitting jobs to a cluster that matches specified cluster labels. Also see Submitting a Dataproc job.

March 01, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 2 weeks on March 15, 2021.

February 26, 2021

New sub-minor versions of Dataproc images: 1.3.85-debian10, 1.3.85-ubuntu18, 1.4.56-debian10, 1.4.56-ubuntu18, 1.5.31-centos8, 1.5.31-debian10, 1.5.31-ubuntu18, 2.0.4-debian10, and 2.0.4-ubuntu18

Image 2.0: Upgraded Spark to 3.1.1 RC2 version

Allow stopping clusters that have autoscaling enabled, and allow enabling autoscaling on clusters that are STOPPED, STOPPING, or STARTING. If you stop a cluster that has autoscaling enabled, the Dataproc autoscaler will stop scaling the cluster. It will resume scaling the cluster once it has been started again. If you enable autoscaling on a stopped cluster, the autoscaling policy will only take effect once the cluster has been started (see Starting and stopping clusters).

Deactivated mysql and hive-metastore components for clusters created with a Dataproc Metastore service on an image that has the DISABLE_COMPONENT_HIVE_METASTORE and DISABLE_COMPONENT_MYSQL capabilities.

Image 1.3 - 1.5: HIVE-18871: hive on Tez execution error due to set hive.aux.jars.path to hdfs://

February 22, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 3 weeks on March 15, 2021.

February 16, 2021

New sub-minor versions of Dataproc images: 1.3.84-debian10, 1.3.84-ubuntu18, 1.4.55-debian10, 1.4.55-ubuntu18, 1.5.30-centos8, 1.5.30-debian10, 1.5.30-ubuntu18, 2.0.3-debian10, and 2.0.3-ubuntu18

Fixed a bug that prevented Dataproc on GKE cluster creation.

February 15, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 4 weeks on March 15, 2021.

February 09, 2021

New sub-minor versions of Dataproc images: 2.0.2-debian10, and 2.0.2-ubuntu18.

Image 2.0:

  • Upgraded Spark built-in Hive to version 2.3.8.
  • Upgraded Druid to version 0.20.1
  • HIVE-24436: Fixed Avro NULL_DEFAULT_VALUE compatibility issue.
  • SQOOP-3485: Fixed Avro NULL_DEFAULT_VALUE compatibility issue.
  • SQOOP-3447: Removed usage of org.codehaus.jackson and org.json packages.

Fixed a bug for beta clusters using a Dataproc Metastore Service where using a subnetwork for the cluster resulted in an error.

February 08, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 5 weeks on March 15, 2021.

February 01, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 3 weeks on February 22, 2021.

January 29, 2021

New sub-minor versions of Dataproc images: 1.3.83-debian10, 1.3.83-ubuntu18, 1.4.54-debian10, 1.4.54-ubuntu18, 1.5.29-centos8, 1.5.29-debian10, 1.5.29-ubuntu18, 2.0.1-debian10, and 2.0.1-ubuntu18.

Image 2.0:

January 25, 2021

Dataproc 2.0 image version will become a default Dataproc image version in 4 weeks on February 22, 2021.

January 22, 2021

Announcing the General Availability (GA) release of Dataproc 2.0 images. This image will become the default Dataproc image version on February 22, 2021.

2.0 image clusters:

You can no longer pass the dataproc:dataproc.worker.custom.init.actions.mode property when creating a 2.0 image cluster. For 2.0+ image clusters, dataproc:dataproc.worker.custom.init.actions.mode is set to RUN_BEFORE_SERVICES. For more information, see Important considerations and guidelines—Initialization processing.

2.0 image clusters:

In 2.0 clusters, yarn.nm.liveness-monitor.expiry-interval-ms is set to 15000 (15 seconds). If the resource manager does not receive a heartbeat from a NodeManager during this period, it marks the NodeManager as LOST. This setting is important for clusters that use preemptible VMs. Usually, NodeManagers unregister with the resource manager when their VMs shut down, but in rare cases when they are be shut down ungracefully, it is important for the resource manager to notice this quickly.

New sub-minor versions of Dataproc images: 1.3.82-debian10, 1.3.82-ubuntu18, 1.4.53-debian10, 1.4.53-ubuntu18, 1.5.28-centos8, 1.5.28-debian10, 1.5.28-ubuntu18, 2.0.0-debian10, and 2.0.0-ubuntu18.

Fixed bug affecting cluster scale-down: If Dataproc was unable to verify whether a master node exists, for example when hitting Compute Engine read quota limits, it would erroneously put the cluster into an ERROR state.

January 15, 2021

Announcing the Beta release of Dataproc Service Account Based Secure Multi-tenancy, which allows you to share a cluster with multiple users. With secure multi-tenancy, users can submit interactive workloads to the cluster with isolated user identities.

New sub-minor versions of Dataproc images: 1.3.81-debian10, 1.3.81-ubuntu18, 1.4.52-debian10, 1.4.52-ubuntu18, 1.5.27-centos8, 1.5.27-debian10, 1.5.27-ubuntu18, 2.0.0-RC23-debian10, and 2.0.0-RC23-ubuntu18.

Image 2.0 preview:

  • Upgraded Spark to version 3.1.0 RC1.

  • Upgraded Zeppelin to version 0.9.0.

  • Upgraded Cloud Storage Connector to version 2.2.0.

  • Upgraded JupyterLab to version 3.0.

The gcloud_dataproc_personal_cluster.py tool for the personal auth beta is no longer supported for new images. It will be replaced by an equivalent set of commands in an upcoming gcloud release.

January 12, 2021

Added support for user configuration of Compute Engine Shielded VMs in a Dataproc Cluster.

January 08, 2021

Added support for new persistent disk type, pd-balanced.

New sub-minor versions of Dataproc images: 1.3.80-debian10, 1.3.80-ubuntu18, 1.4.51-debian10, 1.4.51-ubuntu18, 1.5.26-centos8, 1.5.26-debian10, 1.5.26-ubuntu18, 2.0.0-RC22-debian10, and 2.0.0-RC22-ubuntu18.

Image 2.0 preview:

  • Upgraded Delta Hive connector to version 0.2.0.
  • Upgraded Flink to version 1.12.0.
  • Updated Iceberg to version 0.10.0.

Image 2.0 preview:

HIVE-21646: Tez: Prevent TezTasks from escaping thread logging context

December 17, 2020

New sub-minor versions of Dataproc images: 1.3.79-debian10, 1.3.79-ubuntu18, 1.4.50-debian10, 1.4.50-ubuntu18, 1.5.25-centos8, 1.5.25-debian10, 1.5.25-ubuntu18, 2.0.0-RC21-debian10, and 2.0.0-RC21-ubuntu18.

Image 2.0 preview:

Changed the default value of Spark SQL property spark.sql.autoBroadcastJoinThreshold to 0.75% of executor memory.

Fixed SPARK-32436: Initialize numNonEmptyBlocks in HighlyCompressedMapStatus.readExternal

Image 1.4-1.5:

Fixed a NullPointerException in a primary worker shuffle when the BypassMergeSortShuffleWriter is used when some output partitions are empty.

Images 1.5-2.0 preview:

Fixed ZOOKEEPER-1936: Server exits when unable to create data directory due to race condition.

Fixed a bug where Dataproc agent logs had separate entries for exception stack trace in StackDriver.

December 15, 2020

Announcing the Beta release of the Dataproc cluster Stop/Start.

Announcing the General Availability (GA) release of the Dataproc Workflow Timeout feature, which allows users to set a timeout on their graph of jobs and automatically cancel their workflow after a specified period.

December 08, 2020

Restartable jobs: Added the ability for users to specify the maximum number of total failures when a job is submitted.

Image 2.0 preview

  • Using the n1-standard-1 machine type is no longer supported.

  • Changed default values of Spark SQL properties:

    • spark.sql.adaptive.enabled=true
    • spark.sql.autoBroadcastJoinThreshold =< 2% of executor memory.

The Dataproc Metastore Service is now available in the us-east4, europe-west2, asia-northeast1, and australia-southeast1 regions in addition to the existing us-central1 region.

New sub-minor versions of Dataproc images: 1.3.78-debian10, 1.3.78-ubuntu18, 1.4.49-debian10, 1.4.49-ubuntu18, 1.5.24-debian10, 1.5.24-ubuntu18, 2.0.0-RC20-debian10, and 2.0.0-RC20-ubuntu18.

Image 1.5:

November 16, 2020

New sub-minor versions of Dataproc images: 1.3.77-debian10, 1.3.77-ubuntu18, 1.4.48-debian10, 1.4.48-ubuntu18, 1.5.23-debian10, 1.5.23-ubuntu18, 2.0.0-RC19-debian10, and 2.0.0-RC19-ubuntu18.

Image 2.0 preview

  • Upgraded Hue to version 4.8.0

November 09, 2020

Clusters that use Dataproc Metastore must be created in the same region as the Dataproc Metastore service that they will use.

New sub-minor versions of Dataproc images: 1.3.76-debian10, 1.3.76-ubuntu18, 1.4.47-debian10, 1.4.47-ubuntu18, 1.5.22-debian10, 1.5.22-ubuntu18, 2.0.0-RC18-debian10, and 2.0.0-RC18-ubuntu18.

Image 2.0 preview

Fixed a bug where the Jupyter optional component depended on the availability of GitHub at cluster creation time.

October 30, 2020

Added a dataproc:dataproc.cooperative.multi-tenancy.user.mapping cluster property which takes a list of comma-separated user-to-service account mappings. If a cluster is created with this property set, when a user submits a job, the cluster will attempt to impersonate the corresponding service account when accessing Cloud Storage through the Cloud Storage connector. This feature requires Cloud Storage connector version 2.1.4 or higher.

New sub-minor versions of Dataproc images: 1.3.75-debian10, 1.3.75-ubuntu18, 1.4.46-debian10, 1.4.46-ubuntu18, 1.5.21-debian10, 1.5.21-ubuntu18, 2.0.0-RC17-debian10, and 2.0.0-RC17-ubuntu18.

Fixed a bug in HBASE optional component on HA clusters in which hbase.rootdir was always configured to be hdfs://${CLUSTER_NAME}-m-0:8020/hbase, which assumes that master 0 is the active namenode. Now it is configured to be hdfs://${CLUSTER_NAME}:8020/hbase, so that the active master is always chosen.

Image 1.3 to 2.0 preview:

Fixed HIVE-19202: CBO failed due to NullPointerException in HiveAggregate.isBucketedInput().

Image 2.0 preview:

Fixed HADOOP-15124: Slow FileSystem.Statistics counters implementation.

October 23, 2020

Decreased the minimum allowed value of Dataproc Scheduled Deletion LifecycleConfig.idleDeleteTtl (Dataproc API) and --max-idle flag (gcloud command-line tool) from 10 minutes to 5 minutes.

New sub-minor versions of Dataproc images: 1.3.74-debian10, 1.3.74-ubuntu18, 1.4.45-debian10, 1.4.45-ubuntu18, 1.5.20-debian10, 1.5.20-ubuntu18, 2.0.0-RC16-debian10, and 2.0.0-RC16-ubuntu18.

2.0 preview image versions:

Pin MySQL Java connector version to prevent breakage of the /usr/share/java/mysql-connector-java.jar symlink on long-running and old clusters caused by auto-upgrade to a new MySQL Java connector.

Sole-tenant node cluster create or update requests to use preemptible secondary workers or attach autoscaling policies that create preemptible secondary workers are now correctly rejected.

All image versions:

  • Fixed a bug where files uploaded to Cloud Storage through the JupyterLab UI were incorrectly base64 encoded.

1.4 and 1.5 image versions:

  • SPARK-32708: Fixed SparkSQL query optimization failure to reuse exchange with DataSourceV2.

October 22, 2020

Announcing the Alpha release of the Dataproc Persistent History Server, which provides a UI to view job history for jobs run on active and deleted Dataproc clusters.

October 19, 2020

October 16, 2020

October 13, 2020

New sub-minor versions of Dataproc images: 1.3.72-debian10, 1.3.72-ubuntu18, 1.4.43-debian10, 1.4.43-ubuntu18, 1.5.18-debian10, 1.5.18-ubuntu18, 2.0.0-RC14-debian10, and 2.0.0-RC14-ubuntu18.

October 06, 2020

New sub-minor versions of Dataproc images: 1.3.71-debian10, 1.3.71-ubuntu18, 1.4.42-debian10, 1.4.42-ubuntu18, 1.5.17-debian10, 1.5.17-ubuntu18, 2.0.0-RC13-debian10, and 2.0.0-RC13-ubuntu18.

Image 1.4

Image 1.5

  • Upgraded Spark to version 2.4.7.
  • Installed google-cloud-bigquery-storage package by default in the Anaconda component.
  • Changed default value of zeppelin.notebook.storage in zeppelin-site.xml to "org.apache.zeppelin.notebook.repo.GCSNotebookRepo".

Image 2.0

  • Updated HBase to version 2.2.6.
  • Installed google-cloud-bigquery-storage in default conda environment.
  • Changed default value of zeppelin.notebook.storage in zeppelin-site.xml to "org.apache.zeppelin.notebook.repo.GCSNotebookRepo".

October 01, 2020

Launched Dataproc integration with Compute Engine sole-tenant nodes, which allows users to create a cluster in a sole-tenant node group.

September 30, 2020

Creating clusters and instantiating workflow requests that succeed even when the requester did not have ActAs permission on the service account now generate a warning field in the audit log request.

New sub-minor versions of Dataproc images: 1.3.70-debian10, 1.3.70-ubuntu18, 1.4.41-debian10, 1.4.41-ubuntu18, 1.5.16-debian10, 1.5.16-ubuntu18, 2.0.0-RC12-debian10, and 2.0.0-RC12-ubuntu18.

All supported images

Upgraded Conscrypt to the 2.5.1 version.

Image 1.5

Image 1.5 and Image 2.0 Preview

Image 2.0 preview

  • YARN-9607: Auto-configuring rollover-size of IFile format for non-appendable filesystems.

  • YARN-9525: IFile format is not working against s3a remote folder.

September 18, 2020

New sub-minor versions of Dataproc images: 1.3.69-debian10, 1.3.69-ubuntu18, 1.4.40-debian10, 1.4.40-ubuntu18, 1.5.15-debian10, 1.5.15-ubuntu18, 2.0.0-RC11-debian10, and 2.0.0-RC11-ubuntu18.

All image versions

Image 2.0 preview

September 11, 2020

Added the PrivateIpv6GoogleAccess API field to allow configuring IPv6 access to Dataproc cluster.

New sub-minor versions of Dataproc images: 1.3.68-debian10, 1.3.68-ubuntu18, 1.4.39-debian10, 1.4.39-ubuntu18, 1.5.14-debian10, 1.5.14-ubuntu18, 2.0.0-RC10-debian10, and 2.0.0-RC10-ubuntu18.

1.3-1.5 Images:

HIVE-18323: Vectorization: add the support of timestamp in VectorizedPrimitiveColumnReader for parquet

1.5 and 2.0 preview images:

Upgraded the jupyter-core and jupyter-client packages in the 1.5 and 2.0 images to be compatible with the installed notebook package version.

2.0 preview image:

Fixed a regression that could cause clusters to fail to start if user-supplied keystore/truststore are provided when enabling Kerberos.

September 04, 2020

Switched 1.3 and 1.3-debian image version aliases to point to 1.3 Debian 10 images.

When Enhanced Flexibility Mode is enabled, increased app master, task, and Spark stage retries to 10 to improve resiliency of applications to downscaling and preemption of preemptible VMs.

Support more than 8 local SSDs on VMs. Compute Engine supports 16 and 24 SSDs for larger machine types.

Changed secondary workers default boot disk size to 1000 GB in clusters created with 2.0 preview images.

Improved node memory utilization in clusters created with 2.0 preview images.

August 28, 2020

Launched Dataproc Workflow Timeout feature, which allows users to set a timeout on their graph of jobs and automatically cancel their workflow after a specified period.

Dataproc Metastore integration, which allows users to create a cluster using a Dataproc Metastore service as an external metastore, is now available for Alpha release testing.

August 21, 2020

Announcing the Beta release of Dataproc Enhanced Flexibility Mode (EFM), which manages shuffle data to minimize job progress delays caused by the removal of nodes from a running cluster.

New sub-minor versions of Dataproc images: 1.3.67-debian10, 1.3.67-ubuntu18, 1.4.38-debian10, 1.4.38-ubuntu18, 1.5.13-debian10, 1.5.13-ubuntu18, 2.0.0-RC9-debian10, and 2.0.0-RC9-ubuntu18.

Image 1.3 and 1.4: upgraded the Cloud Storage connector to version to 1.9.18.

Changed 1.4 and 1.4-debian image version aliases to point to 1.4-debian10. The version name 1.4-debian9 will continue to be available, but it won't get updates in future releases.

August 17, 2020

Launched new Personal Cluster Authentication feature, which allows the creation of single-user clusters that can access Cloud Storage using the user's own credentials instead of a VM service account.

August 14, 2020

Dataproc quotas are now regional: each region now has its own quota, which can be separately adjusted. All existing quota overrides have been migrated; customer action is not required.

Enabled Spark SQL parquet metadata cache (removed spark.sql.parquet.cacheMetadata=false from Spark default configuration).

New sub minor versions of Dataproc images: 1.3.66-debian10, 1.3.66-ubuntu18, 1.4.37-debian10, 1.4.37-ubuntu18, 1.5.12-debian10, 1.5.12-ubuntu18, 2.0.0-RC8-debian10, and 2.0.0-RC8-ubuntu18.

Image 1.4:

  • Fixed a bug in Spark EFM HCFS shuffle where failures after partial commits are not recoverable.
  • Upgraded Spark to 2.4.6 version.

Image 1.5:

  • Fixed a bug in Spark EFM HCFS shuffle where failures after partial commits are not recoverable.
  • Upgraded Spark to 2.4.6 version.
  • Upgraded Zeppelin to 0.9.0-preview2 version.
  • Included all plugins in Zeppelin installation by default.

Image 2.0 preview:

August 03, 2020

Dataproc users are required to have service account ActAs permission to deploy Dataproc resources, for example, to create clusters and submit jobs. See Managing service account impersonation for more information.

Opt-in for existing Dataproc customers: This change does not automatically apply to current Dataproc customers without ActAs permission. To opt in, see Securing Dataproc, Dataflow, and Cloud Data Fusion.

July 31, 2020

Enabled Kerberos automatic-configuration feature. When creating a cluster, users can enable Kerberos by setting the dataproc:kerberos.beta.automatic-config.enable cluster property to true. When using this feature, users do not need to specify the Kerberos root principal password with the --kerberos-root-principal-password and --kerberos-kms-key-uri flags.

New sub-minor versions of Dataproc images: 1.3.65-debian10, 1.3.65-ubuntu18, 1.4.36-debian10, 1.4.36-ubuntu18, 1.5.11-debian10, 1.5.11-ubuntu18, 2.0.0-RC7-debian10, and 2.0.0-RC7-ubuntu18.

1.3+ images (includes Preview image):

  • HADOOP-16984: Added support to read history files only from the done directory.

  • MAPREDUCE-7279: Display the Resource Manager name on the HistoryServer web page.

  • SPARK-32135: Show the Spark driver name on the Spark history web page.

  • SPARK-32097: Allow reading Spark history log files via the Spark history server from multiple directories.

Images 1.3 - 1.5:

  • HIVE-20600: Fixed Hive Metastore connection leak.

Images 1.5 - 2.0 preview:

Fixed an issue where optional components that depend on HDFS failed on single node clusters.

Fixed an issue that caused workflows to be stuck in the RUNNING state when managed clusters (created by the workflow) were deleted while the workflow was running.

July 24, 2020

Terminals started in Jupyter and JupyterLab now use login shells. The terminals behave as if you SSH'd into the cluster as root.

Upgraded the jupyter-gcs-contents-manager package to the latest version. This upgrade includes a bug fix to a 404 (NOT FOUND) error message that was issued in response to an attempt to create a file in the virtual top-level directory instead of the expected 403 (PERMISSION DENIED) error message.

New sub-minor versions of Dataproc images: 1.3.64-debian10, 1.3.64-ubuntu18, 1.4.35-debian10, 1.4.35-ubuntu18, 1.5.10-debian10, 1.5.10-ubuntu18, 2.0.0-RC6-debian10, and 2.0.0-RC6-ubuntu18.

Fixed a bug in which the HDFS DataNode daemon was enabled on secondary workers but not started (except on VM reboot if started automatically by systemd).

Fixed a bug in which StartLimitIntervalSec=0 appeared in the Service section instead of the Unit section for systemd services, which disabled rate limiting for retries when systemd restarted a service.

July 17, 2020

Dataproc now uses Shielded VMs for Debian 10 and Ubuntu 18.04 clusters by default.

The Proxy-Authorization header is accepted in place of Authorization to authenticate to Component Gateway to the backend for programmatic API calls. If Proxy-Authorization is set to a bearer token, Component Gateway will forward the Authorization header if it does not contain a bearer token.

For example, this allows setting both Proxy-Authorization: Bearer <google-access-token> as well as setting Authorization: Basic ... to authenticate to HiveServer2 with HTTP basic auth.

Added support for Zeppelin Spark and shell interpreters in Kerberized clusters by default.

New sub-minor versions of Dataproc images: 1.3.63-debian10, 1.3.63-ubuntu18, 1.4.34-debian10, 1.4.34-ubuntu18, 1.5.9-debian10, 1.5.9-ubuntu18, 2.0.0-RC5-debian10, and 2.0.0-RC5-ubuntu18.

Image 2.0 preview:

If a project's regional Dataproc staging bucket is manually deleted, it will be recreated automatically when a cluster is subsequently created in that region.

July 10, 2020

Added --temp-bucket flag to gcloud dataproc clusters create and gcloud dataproc workflow-templates set-managed-cluster to allow users to configure a Cloud Storage bucket that stores ephemeral cluster and jobs data, such as Spark and MapReduce history files.

Extended Jupyter to support notebooks stored on VM persistent disk. This change modifies the Jupyter contents manager to create two virtual top-level directories, named GCS, and Local Disk. The GCS directory points to the Cloud Storage location used by previous versions, and the Local Disk directory points to the persistent disk of the VM running Jupyter.

Dataproc images now include the oauth2l command line tool. The tool is installed in /usr/local/bin, which is available to all users in the VM.

New sub-minor versions of Dataproc images: 1.2.102-debian9, 1.3.62-debian9, 1.4.33-debian9, 1.3.62-debian10, 1.4.33-debian10, 1.5.8-debian10, 1.3.62-ubuntu18, 1.4.33-ubuntu18, 1.5.8-ubuntu18, 2.0.0-RC4-debian10, 2.0.0-RC4-ubuntu18

  • Images 1.3 - 1.5:

    • Fixed HIVE-11920: ADD JAR failing with URL schemes other than file/ivy/hdfs.

  • Images 1.3 - 2.0 preview:

    • Fixed TEZ-4108: NullPointerException during speculative execution race condition.

Fixed a race condition that could nondeterministically cause Hive-WebHCat to fail at startup when HBase is not enabled.

July 07, 2020

Announcing the General Availability (GA) release of Dataproc Component Gateway, which provides secure access to web endpoints for Dataproc default and optional components.

June 24, 2020

New subminor image versions: 1.2.100-debian9, 1.3.60-debian9, 1.4.31-debian9, 1.3.60-debian10, 1.4.31-debian10, 1.5.6-debian10, 1.3.60-ubuntu18, 1.4.31-ubuntu18, 1.5.6-ubuntu18, preview 2.0.0-RC2-debian10, and preview 2.0.0-RC2-ubuntu18.

  • Image 2.0 preview:

    • SPARK-22404: set spark.yarn.unmanagedAM.enabled property to true on clusters where Kerberos is not enabled to run Spark Application Master in driver (not managed in YARN) to improve job execution time.

    • Updated R version to 3.6

    • Updated Spark to 3.0.0 version

  • Image 1.5

    • Updated R version to 3.6

Fixed a quota validation bug where accelerator counts were squared before validation -- for example, previously if you requested 8 GPUs, Dataproc validated whether your project had quota for 8^2=64 GPUs.

June 11, 2020

Users can now configure a tempBucket in API calls. The temp bucket is a Cloud Storage bucket used to store ephemeral cluster and jobs data, such as Spark and MapReduce history files. If you do not specify a temp bucket, Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's temp bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket.

  • New subminor image versions: 1.2.99-debian9, 1.3.59-debian9, 1.4.30-debian9, 1.3.59-debian10, 1.4.30-debian10, 1.5.5-debian10, 1.3.59-ubuntu18, 1.4.30-ubuntu18, and 1.5.5-ubuntu18.

  • New preview image 2.0.0-RC1-debian10, 2.0.0-RC1-ubuntu18, with the following components:

    • Anaconda 2019.10
    • Atlas 2.0.0
    • Druid 0.18.1
    • Flink 1.10.1
    • Hadoop 3.2.1
    • HBase 2.2.4
    • Hive 3.1.2 (with LLAP support)
    • Hue 4.7.0
    • JupyterLab 2.1.0
    • Kafka 2.3.1
    • Miniconda3 4.8.3
    • Pig 0.18.0
    • Presto SQL 333
    • Oozie 5.2.0
    • R 3.6.0
    • Ranger 2.0.0
    • Solr 8.1.1
    • Spark 3.0.0
    • Sqoop 1.5.0
    • Zeppelin 0.9.0

  • Image 1.3+

    • Patched HIVE-23496 Adding a flag to disable materialized views cache warm up.

Druid's Historical's and Broker's JVM and runtime properties are now calculated using server resources. Previously, only the Historical's and MiddleManager's MaxHeapSize property was calculated using server resources. This change modifies how new values for MaxHeapSize and MaxDirectMemorySize properties are calculated for Broker and Historical processes. Also, new runtime properties druid.processing.numThreads and druid.processing.numMergeBuffers are calculated using server resources.

If the project-level staging bucket is manually deleted, it will be recreated when a cluster is created.

Dataproc Job container logging now supports Dataproc Kerberized clusters.

Image 1.5:

  • Fixed a bug that prevented users from logging on to the Presto UI when using Component Gateway.

June 08, 2020

Dataproc is now available in the asia-southeast2 region (Jakarta).

May 27, 2020

Dataproc now provides beta support for Dataproc Hub.

May 21, 2020

You can now set core:fs.defaultFS to a location in Cloud Storage (for example, gs://bucket) when creating a cluster to set Cloud Storage as the default filesystem. This also sets core:fs.gs.reported.permissions, the reported permission returned by the Cloud Storage connector for all files, to 777. If Cloud Storage is not set as the default filesystem, this property will continue to return 700, the default value.

Image 1.4 and 1.5

HADOOP-16984: Enable persistent history server to read from done directory.

New sub-minor versions of Dataproc images: 1.2.98-debian9, 1.3.58-debian9, 1.4.29-debian9, 1.3.58-debian10, 1.4.29-debian10, 1.5.4-debian10, 1.3.58-ubuntu18, 1.4.29-ubuntu18, 1.5.4-ubuntu18.

Image 1.3, 1.4, and 1.5

  • Restrict Jupyter, Zeppelin, and Knox to only accept connections from localhost when Component Gateway is enabled. This restriction reduces the risk of remote code execution over unsecured notebook server APIs. To override this change, when you create the cluster, set the Jupyter, Zeppelin, and Knox cluster properties, respectively, as follows: dataproc:jupyter.listen.all.interfaces=true, zeppelin:zeppelin.server.addr=0.0.0.0, and knox:gateway.host=0.0.0.0.

  • Upgrade Hive to version 2.3.7.

Image 1.4 and 1.5

SPARK-29367: Add ARROW_PRE_0_15_IPC_FORMAT=1 in yarn-env.sh to fix the Pandas UDF issue with pyarrow 0.15.

Image 1.5

Hide the "Quit" button from Jupyter notebook (c.NotebookApp.quit_button = False) when using the Jupyter optional component. The Jupyter environment is shut down when the cluster is deleted.

Set the hive.localize.resource.num.wait.attempts property to 25 to improve reliability of Hive queries.

Image 1.5

Fix a race condition in which hbase-master would try to write /hbase/.tmp/hbase.version to HDFS before HDFS was initialized. This can increase cluster creation time for clusters created with HBase.

  • Fix a race condition in which, when the am.primary_only property is provided, the "non-preemptible" node label was not added to the resource manager's node label store before node managers started registering with the resource manager.

  • Store resource manager node labels in Cloud Storage when am.primary_only property is provided.

The dataproc:alpha.state.shuffle.hcfs.enabled cluster property has been deprecated. To enable Enhanced Flexibility Mode (EFM) for Spark, set dataproc:efm.spark.shuffle=hcfs. To enable EFM for MapReduce, set dataproc:efm.mapreduce.shuffle=hcfs.

May 05, 2020

Clusters can now be created with non-preemptible secondary workers.

May 01, 2020

Announcing the Beta release of Dataproc Component Gateway, which provides secure access to web endpoints for Dataproc default and optional components.

April 27, 2020

Dataproc on GKE version 1.4.27-beta is available with minor fixes.

April 24, 2020

Image 1.5

Delta Lake version is upgraded to 0.5.0 release. Delta Lake Hive Connector 0.1.0 is also added to the 1.5 image.

Customers can now adjust the amount of time the Dataproc startup script will wait for Presto Coordinator service to start before deciding that their startup has succeeded. This is set via dataproc:startup.component.service-binding-timeout.presto-coordinator property and takes a value in seconds. The maximum respected value is 1800 (30 minutes).

New sub-minor image versions: 1.2.96-debian9, 1.3.56-debian9, 1.4.27-debian9, 1.3.56-debian10, 1.4.27-debian10, 1.5.2-debian10, 1.3.56-ubuntu18, 1.4.27-ubuntu18, 1.5.2-ubuntu18

Image 1.5

Cloud Storage connector upgraded to version 2.1.2 (for more information, review the change notes in the GitHub repository)

Image 1.5

Notebook bug fixes: fixed a bug in Zeppelin and Jupyter that resulted in a failure to render images when using Component Gateway. Also fixed a Jupyter Notebooks bug that caused notebook downloads to fail.

April 20, 2020

Dataproc is now available in the us-west4 region (Las Vegas).

April 17, 2020

Announcing the Beta release of Dataproc on Google Kubernetes Engine. Customers can now create Dataproc on GKE clusters to run Spark jobs on Kubernetes via the Dataproc jobs API.

April 15, 2020

Image 1.5

Jupyter on Dataproc now supports exporting notebooks as PDFs.

Image 1.5

Presto now includes two default catalogs:

  • bigquery pointing to the datasets of the cluster's project

  • bigquery_public_data pointing to the public datasets

Image 1.3, 1.4 and 1.5

Added Component Gateway support for Dataproc clusters secured with Kerberos.

New sub-minor versions of Dataproc images: 1.2.95-debian9, 1.3.55-debian9, 1.4.26-debian9, 1.3.55-debian10, 1.4.26-debian10, 1.5.1-debian10, 1.3.55-ubuntu18, 1.4.26-ubuntu18, 1.5.1-ubuntu18.

Image 1.5

Updated Presto to version 331.

Created cloud-sql-proxy log file for the Cloud SQL Proxy initialization action and for Dataproc clusters with Ranger that use Cloud SQL Proxy.

Image 1.3 and 1.4

Debian 10 images will become default images for 1.3 and 1.4 image tracks and Debian 9 images will not be released for these tracks anymore after June 30, 2020.

Images 1.4 and 1.5

SPARK-29080: Support R file extension case-insensitively when submitting Spark R jobs.

Image 1.3, 1.4 and 1.5

Fixed a bug where Jupyter was unable to read and write notebooks stored in Cloud Storage buckets with CMEK enabled.

Image 1.3, 1.4 and 1.5

HIVE-17275: Auto-merge fails on writes of UNION ALL output to ORC file with dynamic partitioning.

April 03, 2020

Added Presto and SparkR job type support to Dataproc Workflows.

Fixed an Auto Zone Placement bug that incorrectly returned INVALID_ARGUMENT errors as INTERNAL errors, and didn't propagate these error messages to the user.

April 01, 2020

Announcing the General Availability (GA) release of Dataproc Presto job type, which can be submitted to a cluster using the gcloud dataproc jobs submit presto command. Note: The Dataproc Presto Optional Component must be enabled when the cluster is created to submit a Presto job to the cluster.

March 25, 2020

Added pagination support to Clusters List methods to provide functionality to the pageSize parameter, which is a part of the API. This feature allows users to specify a page size to receive paginated data in the response. The default page size is 200 and the max page size is 1000.

Added alphabetical sort order to Workflow Templates List methods.

Dataproc clusters can now be created on the GKE platform by setting the GkeClusterConfig instead of the GceClusterConfig via the Beta API. This feature allows jobs to be submitted that will run on the Kubernetes cluster.

Announcing the General Availability (GA) release of Dataproc 1.5 images.

New sub-minor versions of Dataproc images: 1.2.94-debian9, 1.3.54-debian9, 1.4.25-debian9, 1.5.0-debian10, 1.3.54-ubuntu18, 1.4.25-ubuntu18, and 1.5.0-ubuntu18

Image 1.5
Upgraded the Cloud Storage connector to version 2.1.1.

Images 1.2 and 1.4

Dataproc 1.4 will be the default image version after April 31, 2020.

Dataproc 1.2 will have no further releases after June 30, 2020.

Images 1.3, 1.4, and 1.5
Fixed HDFS UI in the Component Gateway on HA clusters

Fixed issue where Jupyter hangs when loading a directory containing many large files. This also improves responsiveness when listing directories.

March 18, 2020

Added the following flag to the gcloud dataproc clusters update command:

  • --num-secondary-workers

The following flag to gcloud dataproc clusters update has been deprecated:

  • --num-preemptible-workers

See the related change, above, for the new flag to use in place of this deprecated flag.

March 17, 2020

Added a dataproc:job.history.to-gcs.enabled cluster property that allows persisting MapReduce and Spark history files to the Dataproc temp bucket (default: true for image versions 1.5+). bucket. This property defaults to true for image versions 1.5 and up. Users can overwrite the locations of job history file persistence through the following properties:

  • mapreduce.jobhistory.done-dir
  • mapreduce.jobhistory.intermediate-done-dir *spark.eventLog.dir
  • spark.history.fs.logDirectory

Added support for n2-, c2-, e2-, n2d-, and m2- machine types when using Auto Zone Placement. Previously, users could only specify n1- or custom- machine types when using Auto Zone Placement.

Added a mapreduce.jobhistory.always-scan-user-dir cluster property that enables the MapReduce job history server to read the history files (recommended when writing history files to Cloud Storage). The default is true.

Customers can now enable the Cloud Profiler when submitting a Dataproc job by setting the cloud.profiler.enable property. To use profiling, customers must enable the Cloud Profiler API for their project and create the cluster with --scopes=cloud-platform. The following profiling properties can also be set when submitting a Dataproc job:

  1. cloud.profiler.name: to collect profiler data under the specified name. If not specified, it defaults to the job UUID.

  2. cloud.profiler.service.version: to compare profiler information from different job runs. If not specified, defaults to the job UUID.

New sub-minor versions of Dataproc images: 1.2.93-debian9, 1.3.53-debian9, 1.4.24-debian9, 1.5.0-RC9-debian10, 1.3.53-ubuntu18, 1.4.24-ubuntu18, and 1.5.0-RC9-ubuntu18

Image 1.2, 1.3, 1.4

Upgraded HBase to 1.3.6

Image 1.4, 1.5 preview

Added ARROW_PRE_0_15_IPC_FORMAT=1 for spark-env for pyarrow upgrade from 0.13 to 0.15.

Image 1.5 preview

  • Preinstalled additional Python packages and Jupyter[Lab] extensions to align Jupyter notebook environment with AI Platforms Notebooks when Jupyter optional component is enabled.

  • Upgraded Druid version to 0.17.0

Normalized custom image URLs to a full URL, for example: https://www.googleapis.com/compute/v1/projects/foo-project/global/images/foo-image. The cluster creation API will continue to accept relative names, such as projects/foo-project/global/images/foo-image or foo-image (see Dataproc API doesn't return imageUri in a consistent format).

Cluster list methods now return results in lexical order.

Image 1.3, 1.4, 1.5 preview

Fixed YARN container log links in Component Gateway

March 16, 2020

Announcing the General Availability (GA) release of Dataproc minimum CPU platform.

March 10, 2020

Added the following flags to gcloud dataproc clusters create and gcloud dataproc workflow-templates set-managed-cluster commands:

  • --num-secondary-workers
  • --num-secondary-worker-local-ssds
  • --secondary-worker-boot-disk-size
  • --secondary-worker-boot-disk-type
  • --secondary-worker-accelerator

The following flags to gcloud dataproc clusters create and gcloud dataproc workflow-templates set-managed-cluster commands have been deprecated:

  • --num-preemptible-workers
  • --num-preemptible-worker-local-ssds
  • --preemptible-worker-boot-disk-size
  • --preemptible-worker-boot-disk-type
  • --preemptible-worker-accelerator

See the related change, above, for the new flags to use in place of these deprecated flags.

March 03, 2020

Added a dataproc:yarn.log-aggregation.enabled cluster property that allows turning on YARN log aggregation to a Dataproc temporary bucket (default: true for image versions 1.5+). Users can also set the location of aggregated YARN logs by overwriting the yarn.nodemanager.remote-app-log-dir YARN property.

New sub-minor versions of Dataproc images: 1.2.92-debian9, 1.3.52-debian9, 1.4.23-debian9, 1.5.0-RC8-debian10, 1.3.52-ubuntu18, 1.4.23-ubuntu18, 1.5.0-RC8-ubuntu18

1.5 preview image:

Upgraded the Cloud Storage connector to version 2.0.1.

In addition to the staging bucket, Dataproc now creates a temporary bucket for storing feature-related data with a 90-day retention period per project per region. The bucket name will be of the following form: dataproc-temp-<REGION>-<PROJECT_NUMBER>-<RANDOM_STRING>.

Changed the staging bucket naming scheme for new buckets from dataproc-<UUID>-<REGION> to dataproc-staging-<REGION>-<PROJECT_NUMBER>-<RANDOM_STRING>.

1.3, 1.4, and 1.5 preview images:

Fixed a bug where Component Gateway pages added an additional banner on each page load in some browsers.

February 25, 2020

Added support for attaching GPUs to preemptible workers.

Component Gateway now supports VPC Service Controls.

The Compute Engine API call from the Dataproc backend to check the API-specific quota limit is now enforced. The default Compute Engine API quota limit should be sufficient for most projects. If your project is experiencing Compute Engine API throttling, you can request a higher quota. If your project requires QPS that is higher than the upper quota limit, consider splitting your project into smaller projects.

New sub-minor versions of Dataproc images: 1.2.91-debian9, 1.3.51-debian9, 1.4.22-debian9, 1.5.0-RC7-debian10, 1.3.51-ubuntu18, 1.4.22-ubuntu18, 1.5.0-RC7-ubuntu18

Add OS-family image version aliases: 1.0-debian, 1.1-debian, 1.2-debian, 1.3-debian, 1.3-ubuntu, 1.4-debian, 1.4-ubuntu, preview-debian, preview-ubuntu. Users can now reference these aliases: Example:

gcloud dataproc clusters create $CLUSTER_NAME --image-version=1.4-debian

Increase Dataproc agent buffer size for streaming driver output to Cloud Storage from 60KB to 8MB. This significantly increases streaming throughput: from ~200KBps to ~7MBps. However, it also increases the memory footprint for each job in the Dataproc agent from ~100KB to ~10MB.

Added support for parameterizing numInstances field in Workflow Templates.

Images 1.3, 1.4, & 1.5:

Backport HIVE-16958.

Image 1.2, 1.3, & 1.4:

Upgrade Oozie to 4.3.1 and backport OOZIE-3112.

Image 1.3:

  • Added BigQuery magics for Python2 and PySpark kernels to Dataproc Jupyter notebooks. You can now use the BigQuery Python client library and Pandas in a Jupyter notebook to visualize data in the BigQuery table.The BigQuery client library provides a %%bigquery cell magic, which runs a SQL query and returns the results as a Pandas DataFrame (see Visualizing BigQuery data in a Jupyter notebook https://cloud.google.com/bigquery/docs/visualize-jupyter ). Example:

    %%bigquer SELECT * FROM bigquery-public-data.samples.natality LIMIT 1

  • Upgrade Zeppelin to 0.8.1 version

Image 1.4 & 1.5:

Added BigQuery magics for Python3 and PySpark kernels to Dataproc Jupyter notebooks. You can now use the BigQuery Python client library and Pandas in a Jupyter notebook to visualize data in the BigQuery table.The BigQuery client library provides a %%bigquery cell magic, which runs a SQL query and returns the results as a Pandas DataFrame (see Visualizing BigQuery data in a Jupyter notebook https://cloud.google.com/bigquery/docs/visualize-jupyter ). Example:

%%bigquer SELECT * FROM `bigquery-public-data.samples.natality` LIMIT 1

Images 1.4 & 1.5 :

Upgrade Spark to 2.4.5 version

Fixed the bug that causing update cluster label operations failed on clusters using CMEK on PD.

Image 1.3 & 1.4:

ZEPPELIN-4168: fixed downloading of Maven dependencies in Zeppelin

Backport YARN-9011 to all 1.2, 1.3, 1.4, and 1.5 images. This fixes a race condition in the resource manager that would sometimes cause containers to be killed while performing a graceful decommission.

Fix "YARN available memory" metric when using YARN's FairScheduler. Importantly, this ensures autoscaling works with the FairScheduler.

February 24, 2020

Dataproc is now available in the us-west3 region (Salt Lake City).

February 03, 2020

You can adjust the amount of time the Dataproc startup script will wait for services (currently hive-metastore, hive-server2, hadoop-hdfs-namenode) to bind to ports before deciding that their startup has succeeded. These delays are set via the dataproc:startup.component.service-binding-timeout.hive-metastore, dataproc:startup.component.service-binding-timeout.hive-server2, and dataproc:startup.component.service-binding-timeout.hadoop-hdfs-namenode cluster properties, which take a value in seconds. The maximum recognized value is 1800 seconds (30 minutes).

New sub-minor versions of Dataproc images: 1.2.90-debian9, 1.3.50-debian9, 1.4.21-debian9, 1.5.0-RC6-debian10, 1.3.50-ubuntu18, 1.4.21-ubuntu18, 1.5.0-RC6-ubuntu18.

1.5 preview image:

Add BigQuery connector to Presto SQL

January 31, 2020

Announcing the General Availability (GA) release of Dataproc Scheduled Deletion. This feature provides options to delete a cluster:

  • at a specified future time
  • after a specified cluster idle period
  • after a specified period that starts from the time of submission of the cluster creation request

January 24, 2020

Dataproc is now available in the asia-northeast3 region (Seoul).

January 20, 2020

New sub-minor versions of Dataproc images: 1.2.89-debian9, 1.3.49-debian9, 1.4.20-debian9,1.5.0-RC5-debian10, 1.3.49-ubuntu18, 1.4.20-ubuntu18, 1.5.0-RC5-ubuntu18.

1.2 – 1.4 image updates: * Upgraded Apache Solr to 6.6.6 version

1.5 preview image updates:

  • Upgraded Apache Druid to 0.16.1 version
  • Upgraded Presto SQL to 326 version
  • Upgraded Apache Oozie to 5.2.0 version
  • Added Apache Atlas 1.2.0
  • Set spark.ui.port property to 0 to run Spark UI on random port - removes limit on max number of concurrent Spark jobs (16 by default). Previous behavior can be restored by setting spark.ui.port=4040 property
  • Set yarn.nodemanager.address property to 0.0.0.0:8026 to run YARN Node Manager on the same port - if a Node Manager process restarts (e.g. when a VM is preempted), it shows up as the same node in YARN. Otherwise, you would see both a LOST node for the old port, as well as a new RUNNING node with the new port
  • Set hive.fetch.task.conversion property to none to disable execution of the SELECT * WHERE conditions LIMIT x queries in the job driver
  • Set mapreduce.jobhistory.always-scan-user-dir property to true to enable better support of history files stored on Cloud Storage.
  • Set mapreduce.jobhistory.recovery.store.class property to org.apache.hadoop.mapreduce.v2.hs.HistoryServerLeveldbStateStoreService to reduce HDFS usage
  • Configured default Spark fair scheduling pool in the /etc/spark/conf/fairscheduler.xml configuration file
  • Added R kernel to Jupyter Optional Component

Breaking Change: Modified gcloud beta clusters create command, replacing --reservation-label with --reservation, which accepts the name of the reservation when --reservation-affinity is specific, matching gcloud compute instances create.

Breaking Change: gcloud command-line tool dataproc commands now require the --region flag on each invocation or dataproc/region config property to be set. Set your default Dataproc region via the gcloud config set dataproc/region us-central1 command.

Breaking Change: Reduced default spark.executor.memory by 1MB from 9310 to 9309 on n1-highmem-4 workers to improve YARN bin packing.

January 10, 2020

New sub-minor versions of Dataproc images: 1.2.88-debian9, 1.3.48-debian9, 1.4.19-debian9, 1.5.0-RC4-debian10, 1.3.48-ubuntu18, 1.4.19-ubuntu18, 1.5.0-RC4-ubuntu18.

Component Gateway UIs now include a banner showing the project and cluster name being accessed and a button to sign out of Component Gateway for the cluster.

December 20, 2019

Fixed a bug in UpdateCluster quota validation logic impacting the use of zonal reservations where the resource requirements of new instances being added in an update failed to consider the capacity of unused zonal reservations, and thus would incorrectly return an "insufficient quota" error if the new instances could not fit in the unused quota outside of zonal reservations.

Added additional information into Autoscaler recommendations in Stackdriver logging. In particular each recommendation now includes 1) the minimum and maximum worker counts configured in the autoscaling policy, 2) the graceful decommission timeout (for SCALE_DOWN operations), and 3) additional context into why the autoscaler couldn't add or remove more nodes. For example, it will indicate if it could not scale up further due to available regional or global quotas in the project (SCALING_CAPPED_DUE_TO_LACK_OF_QUOTA).

New sub-minor versions of Cloud Dataproc images:: 1.2.87-debian9, 1.3.47-debian9, 1.4.18-debian9, 1.5.0-RC3-debian10, 1.3.47-ubuntu18, 1.4.18-ubuntu18, 1.5.0-RC3-ubuntu18

New images now install the latest Linux kernel version available in Debian backports repository through linux-image-amd64 meta package.

Disabled noisy Jersey logging in the YARN Timeline Server.

1.5 preview image updates

  • Upgraded Debian OS to Debian 10 (buster)
  • Upgraded Apache Atlas to version 1.2.0
  • Upgraded Apache Solr to version 6.6.6
  • Upgraded Apache Knox to version 1.3.0
  • Backported SPARK-28921: Spark jobs failing on latest versions of Kubernetes (1.15.3, 1.14.6, 1,13.10, 1.12.10, 1.11.10)
  • Enabled HBase optional component in Dataproc beta.
  • Installed Delta Lake 0.4.0 and Apache Iceberg 0.7.0 jars
  • Updated Jupyter Python 3 kernel to add SparkMonitor 0.11 support. To create SparkContext, user can import SparkContext and create SparkContext using an auto-created conf object using sc=SparkContext.getOrCreate(conf=conf). To create SparkSession, user can import SparkSession and use SparkSession.builder.appName("Any Name").getOrCreate()

December 06, 2019

Fixed a bug in using the JupyterLab UI through the Component Gateway, where an error dialog would pop up after 5 minutes saying "Failed to fetch".

Expose Presto UI in under component gateway when Presto Dataproc Optional Component is enabled.

New sub-minor versions of Cloud Dataproc images: 1.2.86-debian9, 1.3.46-debian9, 1.4.17-debian9, 1.5.0-RC2-debian9, 1.3.46-ubuntu18, 1.4.17-ubuntu18, 1.5.0-RC2-ubuntu18

Added a warning when clusters are created with component gateway and kerberos as they are not currently supported together

1.3 image update - Upgraded Hive to version 2.3.6

1.4 image update - Fixed a bug in the Jupyter component that prevented creating text files using the Jupyter and JupyterLab UIs

1.5 preview image update:

November 26, 2019

1.3 and 1.4 images:

  • Cloud Dataproc images in the 1.3 and 1.4 minor version tracks are affected by an issue that causes the YARN Timeline Server to excessively log without proper rotation. This can specifically impact longer running Clusters and Clusters with high traffic of YARN applications (Dataproc Jobs).

  • There is a script that can be run as an initialization action or on live Master Nodes to mitigate this issue on new and running Clusters.

November 15, 2019

  • Allow creation of Dataproc master and worker VMs with Intel Optane DC Persistent memory using dataproc:dataproc.alpha.master.nvdimm.size.gb and dataproc:dataproc.alpha.master.nvdimm.size.gb properties. Note: Optane VMs can only be created in zones with only n1-highmem-96-aep machine type (such as us-central1-f).

  • Support updating Cloud Storage connector version by setting the GCS_CONNECTOR_VERSION metadata key. For example, --metadata GCS_CONNECTOR_VERSION=2.0.0.

  • New Dataproc image versions: 1.2.85-debian9, 1.3.45-debian9, 1.4.16-debian9, 1.3.45-ubuntu18, 1.4.16-ubuntu18, and Preview.

    • Note that Dataproc 1.1 will have no further releases.

  • Update Conscrypt library to 1.4.2

  • Failed Jobs error messages now include a link to the logs in the Cloud Console rather than to the Google Cloud Storage directory containing them.

  • 1.3 image

    • Upgrade Spark to 2.3.4.

  • 1.4 image

    • Upgrade Hive to 2.3.6.
    • Apply SPARK-28921 to prevent Spark jobs from failing on newer versions of Kubernetes (1.15.3, 1.14.6, 1,13.10, 1.12.10, 1.11.10)

  • Preview image

    • Hadoop 2.10
    • Spark 2.4.4
    • Hive 2.3.6
    • Pig 0.17.0
    • Tez 0.9.2
    • Cloud Storage Connector 2.0.0
    • Python 3.7
    • Scala 2.12.0
    • Anaconda3 5.3.0
    • Druid 0.16
    • Hive Webhcat 2.3.2
    • Jupyter 4.5.0
    • Kerberos 1.15.1
    • Presto 324 (prestosql)
    • Zeppelin 0.9.0-SNAPSHOT
    • Zookeeper 3.4.13

Breaking Changes:

  • Dataproc will no longer accept requests to create new clusters using Debian 8 images. Existing clusters that are using Debian 8 can still be used and scaled.

  • The alpha version of the Kerberos optional component option has been removed from the v1beta2 API. To use Kerberos, please configure it via the SecurityConfig message instead.

  • Disallow setting or overriding goog-dataproc-* labels when creating or updating clusters. All attempts to set goog-dataproc-* labels on creation will be ignored. Any existing custom goog-dataproc-* labels on running clusters will be removed if cluster labels are updated, and attempts to add new custom goog-dataproc-* labels to existing clusters will be ignored.

  • Reset autoscaling if the same or a new autoscaling policy is attached to a cluster. E.g. through gcloud dataproc clusters update --autoscaling-policy=<policy-name>. Note that resetting autoscaling does not change the cluster's status. Autoscaling will only run while the cluster's status is RUNNING or UPDATING, and does not work if the cluster is in ERROR. In addition, if the cluster was previously resizing (UPDATING), the autoscaler will not be able to scale the cluster until the previous update operation has completed.

    • Also fixes an issue where autoscaling would not reset correctly if autoscaling was disabled then re-enabled with the same within 30 seconds. Running gcloud dataproc clusters update --disable-autoscaling and then gcloud dataproc clusters update --autoscaling-policy=<same-policy> should now correctly reset autoscaling regardless of how long autoscaling was disabled.

  • Fixed race condition where deleting a cluster shortly after updating it would not delete all of the cluster's VMs

  • Allow compute resource names with an Alpha API version. For example: https://compute.googleapis.com/compute/alpha/projects/my-project/global/networks/my-network.

    • This allows gcloud alpha dataproc clusters create <cluster-name> --network=my-network to succeed, since gcloud sets the compute API version to the same as the gcloud command track.

October 31, 2019

October 04, 2019

September 26, 2019

  • New sub-minor versions of Cloud Dataproc images: 1.1.121-debian9, 1.2.84-debian9, 1.3.44-debian9, 1.4.15-debian9, 1.3.44-ubuntu18, 1.4.15-ubuntu18.

  • Image 1.4

    • Upgraded Spark to 2.4.4.
  • Fixed an issue caused by expired Bigtop APT repo GPG key.

September 24, 2019

September 20, 2019

Added support for specifying images by image family URI when creating Dataproc clusters.

September 03, 2019

  • New sub-minor versions of Cloud Dataproc images: 1.1.120-debian9, 1.2.83-debian9, 1.3.43-debian9, 1.4.14-debian9, 1.3.43-ubuntu18, 1.4.14-ubuntu18.
  • Druid Optional Component can now be configured via druid-broker, druid-overlord, druid-coordinator, druid-historical, and druid-middlemanager property prefixes.
  • Image 1.3
  • Image 1.4

August 23, 2019

  • Image 1.4:
    • The property dataproc:jupyter.hub.enabled can now be used to enable jupyterhub-singleuser (version 1.0.0) when using the JUPYTER optional component. This is intended to be used with DataprocSpawner. Properties dataproc:jupyter.hub.env and dataproc:jupyter.hub.args are populated by the spawner.
  • New sub-minor versions of Cloud Dataproc images: 1.1.119-debian9, 1.2.82-debian9, 1.3.42-debian9, 1.4.13-debian9, 1.3.42-ubuntu18, 1.4.13-ubuntu18.
  • Image 1.4
    • Upgraded Zeppelin to 0.8.1 with fix for compatibility issue with Spark 2.4.
  • Fixed autoscaling issue where autoscaler rounded down the number of nodes to add if scaleUpFactor * pendingMemory was a fractional value. Now, the autoscaler correctly rounds up to ensure that the cluster is large enough to allocate the required percentage of pending memory. For example, previously, with scaleUpFactor = 1.0 and enough pending memory for half a node, the autoscaler did not allocate a new node. Now, the autoscaler will correctly allocate a new node so that the cluster is sufficiently large to allocate all pending YARN containers.
  • Fixed autoscaling Stackdriver logging that reported the wrong jsonPayload type.
  • Fixed an issue where creations of High Availability clusters with Kerberos enabled using Ubuntu images failed.
  • Image 1.4
    • Fixed an issue where Spark jobs failed on 1.4 clusters with Kerberos enabled.

August 09, 2019

  • New sub-minor versions of Cloud Dataproc images: 1.1.118-debian9, 1.2.81-debian9, 1.3.41-debian9, 1.4.12-debian9, 1.3.41-ubuntu18, 1.4.12-ubuntu18.
  • Image 1.3
  • Image 1.4
    • Applied patch for MAPREDUCE-7101 to Hadoop.
    • Upgraded Hive to 2.3.5.
    • Added Sqoop version 1.4.6.
  • Image 1.4
    • Reverted Zeppelin to version 0.8.0 due to an incompatibility between Spark 2.4 and Zeppelin 0.8.1.

July 12, 2019

  • New sub-minor versions of Cloud Dataproc images: 1.1.117-debian9, 1.2.80-debian9, 1.3.40-debian9, 1.4.11-debian9, 1.3.40-ubuntu18, 1.4.11-ubuntu18.

July 02, 2019

  • New sub-minor versions of Cloud Dataproc images: 1.1.116-debian9, 1.2.79-debian9, 1.3.39-debian9, 1.4.10-debian9, 1.3.39-ubuntu18, 1.4.10-ubuntu18.

June 28, 2019

June 20, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.1.115-debian9, 1.2.78-debian9, 1.3.38-debian9, 1.4.9-debian9, 1.3.38-ubuntu18, 1.4.9-ubuntu18
  • Image 1.1:
    • Upgraded Hadoop to 2.7.7
  • Fixed an issue in which a cluster entered an ERROR state if Cloud Dataproc failed during validation of HDFS capacity when scaling down primary workers.
  • Fixed issue in which Spark jobs failed if fs.defaultFS was passed at job submission and the directory /user/spark/eventlog did not exist in the specified FileSystem. The spark event log directory now defaults to hdfs:///user/spark/eventlog without regard to the default FileSystem. Users can override this behavior by setting the properties spark.eventLog.dir and spark.history.fs.logDirectory when creating a cluster or submitting a job.
  • Fixed an issue in which fsck fails on Kerberized clusters, which can defeat cluster downscaling.
  • YARN node labels are now disallowed on autoscaling clusters (yarn:yarn.node-labels.enabled). Non-exclusive node labels are not compatible with autoscaling since they cause YARN to incorrectly report cluster utilization metrics (including pending memory). See YARN-9088
  • Fixed a rare deadlock in agent that stops sending HDFS/YARN metrics to Stackdriver.

June 18, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.1.114-debian9, 1.2.77-debian9, 1.3.37-debian9, 1.4.8-debian9, 1.3.37-ubuntu18, 1.4.8-ubuntu18
  • Added a warning when using the alpha version of Kerberos configuration. Kerberos is now configured on a Dataproc cluster via the KerberosConfig message instead of Dataproc properties and optional components. Create cluster requests that use the Component+Properties mechanism in the clusters API to configure Kerberos will now generate a warning to use KerberosConfig instead.
  • Clusters created with small PD Standard disks will no longer trigger a warning during creation if they also have local SSDs specified on the disk configuration.
  • Audit requests and responses for the Cloud Dataproc Autoscaling Policies API. Previously, API methods were audited, but not the actual request and response bodies.
  • Image 1.3 and 1.4:
    • Cloud Storage connector upgraded to 1.9.17
  • Image 1.3:
    • Upgraded Tez to 0.9.2
  • Image 1.4:
    • Upgraded Spark to 2.4.3
    • Upgraded Flink to 1.6.4
    • Upgraded Zeppelin to 0.8.1
  • Image 1.2, 1.3, and 1.4:
    • Fixed bug where agent would fail to mark jobs as done and complete diagnose requests when Resource Manager requests are slow.

June 11, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.1.113-debian9, 1.2.76-debian9, 1.3.36-debian9, 1.4.7-debian9, 1.3.36-ubuntu18, 1.4.7-ubuntu18
  • Failed autoscaling operations now appear with error messages in logs. Previously, log included only the failing operation ID, which user was expected to use to lookup the error message.
  • Image 1.4:
    • Upgraded Tez to 0.9.2.
  • Image 1.3:
    • The zstandard codec is now supported in Hadoop.

June 01, 2019

June 2019 Release Note Bulletin

This bulletin applies if you override the defaultFS at job-submission time for Spark jobs.

An inadvertent change in behavior has been identified for determining the location of the Spark eventlog directory when setting spark.hadoop.fs.defaultFS to any setting other than HDFS at Spark job-submission time in the following Cloud Dataproc June 2019 image versions:

1.1.113-debian9, 1.2.76-debian9, 1.3.36-debian9, 1.4.7-debian9, 1.3.36-ubuntu18, 1.4.7-ubuntu18 1.1.114-debian9, 1.2.77-debian9, 1.3.37-debian9, 1.4.8-debian9, 1.3.37-ubuntu18, 1.4.8-ubuntu18

Although the /user/spark/eventlog directory normally stays in HDFS, it began referring to the specified filesystem from spark.hadoop.fs.defaultFS in these image versions, and can result in the failure of Spark jobs with an error similar to "java.io.FileNotFoundException: File not found : /user/spark/eventlog".

Use any of the following strategies as a workaround:

  1. Run the following command manually before submitting jobs:

    hdfs dfs -mkdir -p <filesystem base/bucket>/user/spark/eventlog

  2. Add the following Spark properties to Spark jobs to override defaultFS:

    spark.eventLog.dir=hdfs:///user/spark/eventlog,spark.history.fs.logDirectory=hdfs:///user/spark/eventlog

  3. Temporarily pin to the immediately prior image version numbers until image versions newer than those listed above are available.

May 16, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.1.111-debian9, 1.2.74-debian9, 1.3.34-debian9, 1.4.5-debian9, 1.3.34-ubuntu18, 1.4.5-ubuntu18
  • Image 1.1:
    • Parallelized Hive.copyFiles method in Spark's fork of Hive.
    • Resolved scheme-less Spark event log directory relative to default filesystem.
  • Image 1.4:

May 09, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.0.119-debian9, 1.1.110-debian9, 1.2.73-debian9, 1.3.33-debian9, 1.4.4-debian9, 1.3.33-ubuntu18, 1.4.4-ubuntu18
  • This is the final release of Dataproc 1.0 image.
  • Image 1.3 and 1.4:
    • Allow remapping Jupyter and Zeppelin Optional Component ports via dataproc:{jupyter,zeppelin}.port properties
  • Image 1.4:
    • Upgrade Spark to 2.4.2
  • Fixed a rare issue where a managed instance group could be leaked if a delete cluster request is processed while a labels update is in progress for a cluster that uses preemptible VMs.

May 06, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.0.118-debian9, 1.1.109-debian9, 1.2.72-debian9, 1.3.32-debian9, 1.4.3-debian9, 1.3.32-ubuntu18, 1.4.3-ubuntu18
  • Image 1.3:
    • Upgraded Spark to 2.3.3.
  • Image 1.2, 1.3, and 1.4:
  • Image 1.3 and 1.4:

April 29, 2019

  • New major and sub-minor versions of Cloud Dataproc images: 1.0.117-debian9, 1.1.108-debian9, 1.2.71-debian9, 1.3.31-debian9, 1.4.2-debian9, 1.3.31-ubuntu18, 1.4.2-ubuntu18
  • Image 1.2:
    • Parallelized the Hive.copyFiles method in Spark's fork of Hive.
  • Image 1.4:
    • Upgraded Spark to 2.4.1.
    • Included S3 and Azure Storage connectors in Spark 2.4 libraries.
  • Changed compute root API URL from www.googleapis.com to https://compute.googleapis.com due to a change in compute client.
  • Allowed updating clusters after the expiration of its custom image. Previously, after the expiration of a cluster's custom image, the cluster could not be resized manually or through autoscaling. Now, clusters created with valid custom images can be resized indefinitely.
  • Disallowed using the dataproc:am.primary_only cluster property with autoscaling since this property, which restricts the scheduling of app masters to primary workers, uses YARN Node Labels. Non-exclusive node labels are not compatible with autoscaling since they cause YARN to incorrectly report cluster utilization metrics (including pending memory). See YARN-9088 Note: Hadoop MapReduce and Spark jobs in client mode, which is the Cloud Dataproc default, are resilient to app master failures (scheduling app masters on primary workers is not necessary in client mode).
  • Fixed issue where the dataproc.googleapis.com/cluster/job/running_count metric was not consistent with the active running jobs count on the Cloud Dataproc Job page in Google Cloud Platform console.
  • Fixed an issue in which the HDFS Datanode blocks and MapReduce and Spark local directories on clusters with local SSDs were stored on both the cluster's boot disk and on the local SSDs. They are now stored only on the local SSDs.

April 26, 2019

  • Announcing the Beta release of Cloud Dataproc Job Logs in Stackdriver. Enable this feature to view, search, filter, and archive job driver and YARN container logs in Stackdriver Logging.
    • The dataproc:dataproc.logging.stackdriver.job.driver.enable=true service property can now be used to enable sending Job driver logs to Stackdriver. Logs will be sent to the Stackdriver "Cloud Dataproc Job" resource under the dataproc.job.driver log.
    • The dataproc:dataproc.logging.stackdriver.job.yarn.container.enable service property can now be used to enable sending YARN container logs to Stackdriver. Logs will be sent to the Stackdriver "Cloud Dataproc Job" resource under the dataproc.job.yarn.container log (instead of the "Cloud Dataproc Cluster" resource under the yarn-userlogs log).
  • New sub-minor versions of Cloud Dataproc images - 1.0.116-debian9, 1.1.107-debian9, 1.2.70-debian9, 1.3.30-debian9, 1.4.1-debian9, 1.3.30-ubuntu18, 1.4.1-ubuntu18
  • Removed limit on concurrent number of running workflow templates per project.
  • Put Zookeeper Server in secure (Kerberos) mode if Kerberos is enabled on HA clusters.
  • The dataproc:jobs.file-backed-output.enable service property now configures Cloud Dataproc jobs to pipe their output to temporary files in the /var/log/google-dataproc-job directory.
  • Added cluster UUID in the description of Compute Engine instance groups created by Cloud Dataproc to be used as secondary identifier to classify whether a Google Compute Engine instance group manager is created by Cloud Dataproc.
  • Image 1.3 only:
    • Parallelized Hive.copyFiles method in the Spark fork of Hive.
  • Fixed quota validation errors in which scaling down clusters with accelerators on primary workers failed with java.lang.IllegalArgumentException: occurrences cannot be negative.
  • Fixed an issue where the Tez UI failed to load.
  • Fixed a race condition on cluster startup in which a cluster accepted Hive jobs before the hive-server2 was available via beeline to run the jobs.
  • Fixed an issue where removing the yarn.nodemanager.local-dirs property from yarn-site.xml in a Kerberized cluster failed cluster creation.

April 18, 2019

  • Cloud Dataproc is now available in the asia-northeast2 region (Osaka).

April 05, 2019

  • The Cloud Dataproc Component Gateway (Alpha Release) feature can now be enabled from the Cloud Dataproc Create a cluster form on the Google Cloud Platform console. After enabling this feature, the Web Interfaces tab on the Cluster details form on the GCP console lists the Component Gateway links to the web interfaces of default and optional components installed on the cluster. Clicking on a link opens the web interface of the component running on the master node of the cluster in a local browser.

April 04, 2019

  • Initial Alpha release of Cloud Dataproc Enhanced Flexibility Mode. Enhanced Flexibility Mode can provide stability and scalability benefits by preserving stateful node data, such as mapreduce shuffle data, in HDFS. Enhanced Flexibility Mode can be used with clusters created with image version 1.4.x and later.

March 26, 2019

  • Announcing the Alpha release of Cloud Dataproc Component Gateway, which provides secure access to web endpoints for Cloud Dataproc core and optional components without relying on SSH tunnels or modifying firewall rules to allow inbound traffic (applies to clusters created with image version 1.3.29 and later).

March 22, 2019

March 12, 2019

  • Announcing the General Availability (GA) release of Cloud Dataproc Optional Components. This feature allows users to specify additional components to install when creating new Cloud Dataproc clusters (applies to clusters created with image version 1.3 and later).

March 11, 2019

  • Cloud Dataproc is now available in the europe-west6 region (Zürich, Switzerland).

March 08, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.114-deb9, 1.1.105-deb9, 1.2.68-deb9, 1.3.28-deb9, 1.4.0-RC12-deb9
  • Image 1.3 and 1.4 preview
    • Cloud Storage connector upgraded to version 1.9.16.
  • Image 1.4 preview
    • Added Spylon (Scala) kernel for Jupyter.
  • Fixed an issue in which the namenode occasionally prevented datanodes from registering correctly.

March 04, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.113-deb9, 1.1.104-deb9, 1.2.67-deb9, 1.3.27-deb9, 1.4.0-RC11-deb9
  • Image 1.0-1.2
    • YARN-6868: Add test scope to certain entries in hadoop-yarn-server-resourcemanager pom.xml.
  • Image 1.0-1.4 preview
  • Image 1.1-1.4 preview
    • Parallelized files move and deletion in Spark Driver during SQL queries execution:
      • HIVE-20395: Parallelize files move in replaceFiles method.
      • Parallelize Hive.moveFile method.
      • Parallelize FileUtils.trashFilesUnderDir method.
    • Upgraded Zookeeper to 3.4.13 version.
    • Upgraded Hadoop LZO to 0.4.20 version.
  • Image 1.3
    • Added Solr 6.6.0
    • Upgraded Kafka to 1.1.1 version.
    • Upgraded the Cloud Storage connector to 1.9.15 version. Review the change notes in the GitHub repository for more information.
  • Image 1.4 preview
    • Upgraded Solr to 7.6.0 version.
    • Use 1TB sized PD-Standard for masters and primary workers by default to improve I/O performance.
    • Moved Cloud Storage connector to /usr/local/share/google/dataproc/lib directory.
    • Upgraded the Cloud Storage connector to 1.9.15 version. Review the change notes in the GitHub repository for more information.
  • Fixed regression in creating autoscaling clusters where dataproc:alpha.autoscaling.secondary.max_workers had to be greater than 0.

February 26, 2019

  • Due to the issue announced on February 22, 2019, Cloud Dataproc image versions announced on February 14, 2019 (1.0.111-deb9, 1.1.102-deb9, 1.2.65-deb9, 1.3.25-deb9, 1.4.0-RC9-deb9) and the changes and fixes associated with those image versions are currently not available. The latest images versions available for cluster creation, and the changes and fixes associated with those image versions, are those announced on February 11, 2019 (1.0.110-deb9, 1.1.101-deb9, 1.2.64-deb9, 1.3.24-deb9, 1.4.0-RC8-deb9).

February 22, 2019

  • Cloud Dataproc images 1.3.25-deb9 and 1.4.0-RC9-deb9 contain Cloud Storage connector 1.9.13 that has a bug that could lead to a spike in Cloud Storage list requests. You can mitigate this issue by pinning the Dataproc image version to one of the previous releases (1.3.24-deb9, 1.4.0-RC8-deb9).

February 14, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.111-deb9, 1.1.102-deb9, 1.2.65-deb9, 1.3.25-deb9, 1.4.0-RC9-deb9
  • The yarn-site.xml yarn.resourcemanager.webapp.methods-allowed property now defaults to "GET,HEAD". This change restricts the HTTP methods that can be called on the YARN Resource Manager web UI (default port 8088) and REST APIs to GET and HEAD only, and disables job submission and modifications via the YARN REST API. You can override the default values and enable specific HTTP methods on port 8088 by setting the yarn.resourcemanager.webapp.methods-allowed property to one or more comma-separated HTTP method names when you create a cluster. An ALL value will allow all HTTP methods on the port.
    Example: gcloud dataproc clusters create --properties='yarn:yarn.resourcemanager.webapp.methods allowed=GET,POST,DELETE'
    Recommendation: If you set this property to allow non-default HTTP methods, make sure to configure firewall rules and other security settings to restrict access to port 8088 (see Cluster Web Interfaces→Avoid Security Vulnerabilities).
  • Image 1.2 only:
    • Upgraded Spark to 2.2.3
    • HIVE-15208: Query string is now HTML encoded for Web UI
  • Image 1.3 only:
    • Upgraded Flink to 1.5.6
    • The Cloud Storage connector has been upgraded to 1.9.13. Review the change notes in the GitHub repository for more information.
  • Image 1.4 preview only:
    • The cloud Storage connector has been upgraded to 1.9.13. Review the change notes in the GitHub repository for more information.
    • Used Python 3.6 instead of 3.7 as the default user Python version
      • Downgraded default Miniconda3 to 4.5.4
      • Downgraded Anaconda3 optional component to 5.2.0
    • Added Solr 6.6.0
    • HIVE-18786: NPE in Hive windowing functions
    • Upgraded Zookeeper to 3.4.13
    • Upgraded Hadoop LZO to 0.4.20
  • HIVE-20395: Parallelized file moves in replaceFiles method
  • Image 1.1 only:
    • HIVE-16844: Fixed a Connection leak in ObjectStore when new Conf object is used.
  • Image 1.3 and 1.4:
    • Fixed an issue where Jupyter notebook directory is not honored
    • Fixed an issue where PySpark kernel in Jupyter does not use the correct Python version

February 11, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.110-deb9, 1.1.101-deb9, 1.2.64-deb9, 1.3.24-deb9, 1.4.0-RC8-deb9.
  • YARN applications that are submitted via the Cloud Dataproc Jobs API now include the Job UUID in the application tags with the format "dataprocuuid${UUID}".
  • Removed upper limit on total number of threads in job drivers.
  • Image 1.3 only:
    • Added a new yarn-site.xml property (yarn.resourcemanager.webapp.methods-allowed) which is set with a comma- separated list of the names of HTTP methods that the YARN Resource Manager will allow to be called in its web UI and REST API (default port 8088). The current default value is "ALL", which allows all HTTP methods (GET,POST,PUT,PATCH,DELETE,HEAD,CONNECT,OPTIONS, TRACE). It is recommended that this property be set to "GET" to disable remote code submission or other modifications via the REST API. This property will default to "GET" for all Cloud Dataproc clusters in a future release (see Important cross-update notes, above).
  • Image 1.4 preview only:
    • Upgraded Kafka to 1.1.1
    • Added a new yarn-site.xml property (yarn.resourcemanager.webapp.methods-allowed) which is set with a comma- separated list of the names of HTTP methods that the YARN Resource Manager will allow to be called in its web UI and REST API (default port 8088). The current default value is "ALL", which allows all HTTP methods (GET,POST,PUT,PATCH,DELETE,HEAD,CONNECT,OPTIONS, TRACE). It is recommended that this property be set to "GET" to disable remote code submission or other modifications via the REST API. This property will default to "GET" for all Cloud Dataproc clusters in a future release (see Important cross-update notes, above).
  • Fixed issue in which graceful decommission was not graceful on HA clusters.
  • Fixed issue in which mapreduce jobs would fail when trying to write a final history event with "Unknown Job" error by setting dfs.namenode.file.close.num-committed-allowed to 1.

February 01, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.109-deb9, 1.1.100-deb9, 1.2.63-deb9, 1.3.23-deb9, 1.4.0-RC7-deb9.

January 28, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.108-deb9, 1.1.99-deb9, 1.2.62-deb9, 1.3.22-deb9, 1.4.0-RC6-deb9.
  • Fixed a bug that can cause jobs in heavily loaded clusters to fail with a "Task not acquired" error.

January 22, 2019

  • New sub-minor versions of Cloud Dataproc images - 1.0.107-deb9, 1.1.98-deb9, 1.2.61-deb9, 1.3.21-deb9, 1.4.0-RC5-deb9.
  • Do not throttle scheduling of submitted jobs based on master node CPU load.
  • Set yarn.resourcemanager.nodemanager-graceful-decommission-timeout-secs to 86400 (1 day) on Cloud Dataproc 1.3+ clusters. This fixes the bug where trying to graceful decommission nodes with a timeout on Cloud Dataproc 1.3+ would still terminate at 1 hour.
  • Upgrade the Presto Component to version 0.215.
  • Change property parameter in Kerberos Component "dataproc:kerberos.cross-realm-trust.shared-key.uri" to "dataproc:kerberos.cross-realm-trust.shared-password.uri".
  • Make the Presto Component compatible with the Kerberos Component, so if both Components are enabled, Presto will run in secure mode.
  • Explicitly set the property hadoop.ssl.enabled.protocols to "TLSv1,TLSv1.1,TLSv1.2". This change will affect any newly created clusters using a Dataproc image 1.2 and up. This is to help avoid issues caused by incompatibility between SSLv2Hello (enabled by default in Hadoop 2.8.4 and up) and the Conscrypt security provider, the default security provider used by the Cloud Storage connector.
  • Make 1.3 default image version.
  • Image 1.0 only:
    • Fix Hive Metastore/Hive Server2/Spark History Server systemd services exited problem.
  • Image 1.2 only:
    • Upgrade Hue to 4.3.0.
    • Upgrade Hadoop to 2.8.5.
    • Patch [SPARK-21960][STREAMING] Spark Streaming Dynamic Allocation should respect spark.executor.instances.
  • Image 1.3 only:
    • Upgrade Hadoop to 2.9.2.
    • Upgrade Hue to 4.3.0.
    • Patch Spark-25959 GBTClassifier picks wrong impurity stats on loading.
    • Patch HIVE-20395 Parallelize files move in the ql.metadata.Hive#replaceFiles
    • Upgrade Hive to 2.3.4.
    • Cloud Storage connector upgrade (for more information, review the change notes in the GitHub repository).
  • Image 1.4 - Preview only:
    • Upgrade Hadoop to 2.9.2.
    • Upgrade Flink to 1.6.2.
    • Patch Spark-25959 GBTClassifier picks wrong impurity stats on loading.
    • Upgrade Hive to 2.3.4.
    • Cloud Storage connector upgrade (for more information, review the change notes in the GitHub repository).
  • Remove the logic in Kerberos optional component to set property hadoop.ssl.enabled.protocols. It will be set by the Dataproc service.
  • Collect Zookeeper logs as part of the diagnose command.
  • Export Zookeeper logs to stackdriver.
  • Run Dataproc Agent process at higher priority.
  • Add parquet (parquet-cli) binary to PATH for debugging convenience.
  • Fix Hive-WebHCat to use effective python profile, and fix issues with logging directory.
  • Publish up-to-date HDFS and YARN metrics from the Dataproc agent. Earlier, there was an up to 30 second delay between collection and publishing.
  • Reduce the minimum autoscaling cooldown period to 2 minutes. The cooldown period still starts after a previous scaling operation completes.
  • In Kerberos optional component activation process, the KMS key existence verification is collapsed into decryption while using the key.

December 14, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.105-deb9, 1.1.96-deb9, 1.2.59-deb9, 1.3.19-deb9, 1.4.0-RC3-deb9.
  • Allow properties in zoo.cfg to be configured through 'zookeeper:' property prefix.
  • Allow users to parameterize the name of a managed cluster in workflow templates.

December 10, 2018

  • Announcing the General Availability (GA) release of Cloud Dataproc Stackdriver Monitoring. Stackdriver Monitoring is automatically enabled on Cloud Dataproc clusters, and collects and reports HDFS, YARN, and other Cloud Dataproc cluster and job metrics.
  • Announcing a Beta release of Cluster Scheduled Deletion, which updates support of this feature in the Cloud SDK by including scheduled deletion output in the gcloud beta dataproc clusters list and gcloud beta dataproc clusters describe commands.
  • Announcing the Beta release of Cloud Dataproc image version 1.4, which can be specified as "1.4.0-RC2-deb9" or "preview". This new image version includes Python 3.7 installed via Miniconda and Spark 2.4.
  • Announcing the Alpha release of Cloud Dataproc - Kerberos Top-Level Component. This feature enables Kerberos/Hadoop Secure Mode, providing user isolation and encryption inside a Cloud Dataproc cluster created with image version 1.3 and higher.
  • Autoscaling logs now appear in Stackdriver Logging under logs for a Cloud Dataproc cluster.
  • New sub-minor versions of Cloud Dataproc images - 1.0.104-deb9, 1.1.95-deb9, 1.2.58-deb9, 1.3.18-deb9, 1.4.0-RC2-deb9.
  • Upgraded Spark from 2.3.1 to 2.3.2 on image version 1.3.
  • Extra ' character in /etc/hadoop/conf.empty/yarn-site.xml under yarn.application.classpath prevents running Hadoop jobs.
  • Image 1.2 only:
    • Fix issue where difference in featureImportances results on computed vs. saved models. (SPARK-25959).
  • Image 1.3 and later only:
    • Jupyter Optional Component changes default storage location of notebooks from gs://staging-bucket/notebooks to gs://staging-bucket/notebooks/jupyter. This can be changed by setting dataproc:jupyter.notebook.gcs.dir cluster property.
    • Zeppelin Optional Component will now save notebooks to the staging Google Cloud Storage bucket in gs://staging-bucket/notebooks/zeppelin. This can be changed by setting zeppelin:zeppelin.notebook.gcs.dir cluster property.
    • Zeppelin Optional Component can now be configured via zeppelin and zeppelin-env property prefixes.

December 04, 2018

November 16, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.102-deb9, 1.1.93-deb9, 1.2.56-deb9, 1.3.16-deb9.
  • Creating Dataproc clusters will now issue a warning if we detect a potential security vulnerability due to misconfigured firewall rules allowing public access to YARN ports.
  • Looking up the details of a job will show who submitted that job in the submittedBy field.
  • Image 1.3 only:

November 12, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.101-deb9, 1.1.92-deb9, 1.2.55-deb9, 1.3.15-deb9.
  • Minor image versions now redirect to Debian 9-based images. For example, 1.2 now points to 1.2-deb9. There will be no new Debian 8-based images.
  • Job UUIDs are now exposed to allow job runs to be uniquely identified.
  • The Cloud Storage Connector now sets fadvise to SEQUENTIAL for Hadoop DistCp jobs. This mode is optimized for streaming reads, which are most efficient for these workloads.
  • Removed the ALPN boot jar from Cloud Dataproc versions 1.0 and 1.1 due to incompatibility with the latest OpenJDK 8 distributed with Debian. gRPC users must use a form of netty-tcnative, for example, io.grpc:grpc-netty-shaded. This already applies to 1.2 and 1.3.
  • Reduced the Linux process priority of user jobs.
  • dfs.namenode.datanode.registration.retry-hostname-dns-lookup is now set to true.
  • Increased the maximum number of DistCp tasks scheduled per node. This improves DistCp performance.
  • Image 1.3 only:
    • Ported HDFS-13056 to Hadoop 2.9.
    • Upgraded Cloud Storage Connector to version 1.9.9. See the GitHub release notes.
    • Presto is now supported as an optional top-level component.
  • Fixed a bug where CMEK was not passed to PD on preemptible workers. * Fixed a bug where changes to PATH in custom images broke Cloud Dataproc initialization. For example, changing the default Python to Python 3 previously broke initialization. * Fixed a bug where POST ant PUT requests to the YARN REST API were blocked by anonymous users on Cloud Dataproc 1.3. This was fixed by adding org.apache.hadoop.http.lib.StaticUserWebFilter back to hadoop.http.filter.initializers in core-site.xml * Fixed logging warnings in Hive 2 in Cloud Dataproc 1.1, 1.2, and 1.3.

November 02, 2018

  • As of November 2, 2018, Cloud Dataproc has stopped releasing images based on Debian 8. 1.X releases after November 2, 2018 will use Debian 9 as their base OS. No further updates, patches, or security fixes will be released for Debian 8 after November 2, 2018.
  • On November 9, 2018, the ALPN boot jar will be removed from the classpath of future Cloud Datproc version 1.0 and 1.1 images due to incompatibilites with the latest security patches of the Debian OpenJDK 8 package. Image version 1.2 and 1.3 will be gRPC Java clients, and will need to use netty-tcnative for authentication with Google APIs. Clients, such as Cloud Bigtable, that bundle netty-tcnative can depend on grpc-netty-shaded to avoid collisions with the Hadoop Classpath. See Manage Java and Scala dependencies for Apache Spark for more information.

October 26, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.100-deb8, 1.1.91-deb8, 1.2.54-deb8, 1.3.14-deb8, 1.0.100-deb9, 1.1.91-deb9, 1.2.54-deb9, 1.3.14-deb9.
  • Fixed a Graceful Decommissioning and Secondary Workers issue. When using graceful decommissioning to remove secondary (preemptible) workers soon after scaling the secondary worker group, an error would occasionally occur with a error message similar to the following: "Secondary worker group cannot be modified outside of Cloud Dataproc. If you recently created or updated this cluster, wait a few minutes before gracefully decommissioning to allow all secondary instances to join or leave the cluster. Expected secondary worker group size: x, actual size: y."
    Related Information:
    • Cloud Dataproc calls listManagedInstances on the Managed Instance Group that manages secondary workers, filters out instances whose current action is DELETING or ABANDONING, and then chooses instances to delete from the resulting set. Cloud Dataproc prefers to delete VMs that are being created, rather than running VMs.
    • When describing a cluster, the secondary worker group will still appear to have instances that are DELETING and ABANDONING. Thus, the group's target size may not match the size of the list of hostnames, even after the scaling operation is complete. The instances will be removed from the list when they have been deleted from the Managed Instance group.
  • Fixed issues that led to an "Internal Server Error" when creating clusters.

October 22, 2018

  • Cloud Dataproc is now available in the asia-east2 region (Hong Kong).

October 19, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.99-deb8, 1.1.90-deb8, 1.2.53-deb8, 1.3.13-deb8, 1.0.99-deb9, 1.1.90-deb9, 1.2.53-deb9, 1.3.13-deb9.
  • Image 1.0 only: Fixed a bug where Stackdriver metrics were failing to be published, which also impacted autoscaling functionality.

October 12, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.98-deb8, 1.1.89-deb8, 1.2.52-deb8, 1.3.12-deb8, 1.0.98-deb9, 1.1.89-deb9, 1.2.52-deb9, 1.3.12-deb9.
  • Image 1.3 only: Cloud Storage connector upgrade (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to 1.9.8 version.
  • Image 1.0 only: Upgrade Hadoop to 2.7.4.

October 09, 2018

October 05, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.97-deb8, 1.1.88-deb8, 1.2.51-deb8, 1.3.11-deb8, 1.0.97-deb9, 1.1.88-deb9, 1.2.51-deb9, 1.3.11-deb9.
  • Image 1.1 only: Upgraded Zeppelin to 0.7.3.
  • Image 1.1 only: Published YARN and HDFS metrics to Stackdriver (except HDFS PendingDeletionBlocks) from clusters using image version 1.1.82 and above.
  • Fixed an issue in which the timeout for the first initialization action was used as the timeout for all other initialization actions.
  • Fixed infrequent issue in which cluster creation failed with debconf: DbDriver "config": /var/cache/debconf/config.dat is locked by another process: Resource temporarily unavailable error.

September 28, 2018

  • Feature (1.2+) - Enabled new dataproc:am.primary_only cluster property to prevent application master from running on preemptible workers. This feature is only enabled for Dataproc 1.2+ clusters. To use the cluster property, set --properties dataproc:am.primary_only=true when creating a cluster.
  • New sub-minor versions of Cloud Dataproc images - 1.0.97-deb8, 1.1.88-deb8, 1.2.51-deb8, 1.3.11-deb8, 1.0.97-deb9, 1.1.88-deb9, 1.2.51-deb9, 1.3.11-deb9.
  • Image 1.3 only: Cloud Storage connector upgrade (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to 1.9.7 version
  • Image 1.0-1.2 only: Cloud Storage and BigQuery connector upgrades (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to 1.6.10 version
    • BigQuery connector has been upgraded to 0.10.11 version
  • Fixed issue where Spark history server failed to start.
  • Fixed issue where autoscaling stops after 1000 cool-down periods.

September 25, 2018

September 21, 2018

  • Announcing the Beam on Flink on Dataproc Initialization Action (Beta) on GitHub, which sets up an Apache Beam service on a Cloud Dataproc cluster.
  • New sub-minor versions of Cloud Dataproc images - 1.0.95-deb8, 1.1.86-deb8, 1.2.49-deb8, 1.3.9-deb8, 1.0.95-deb9, 1.1.86-deb9, 1.2.49-deb9, 1.3.9-deb9.
  • Changed initialization actions to run inside a login shell so that environment profile changes can be seen by subsequent init actions.
  • Image 1.3 only: Cloud Storage connector upgrade (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to 1.9.6 version
  • Image 1.0-1.2 only: Cloud Storage and BigQuery connector upgrades (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to 1.6.9 version
    • BigQuery connector has been upgraded to 0.10.10 version
  • Fixed issue where gRPC based clients can fail when calling Get/List on Operations after using v1beta2 API to perform cluster operations.

September 14, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.94-deb8, 1.1.85-deb8, 1.2.48-deb8, 1.3.8-deb8, 1.0.94-deb9, 1.1.85-deb9, 1.2.48-deb9, 1.3.8-deb9.
  • Added Flink 1.5.0 and HBase 1.3.2 to 1.3-deb8 images.
  • Improved granularity and accuracy of Hadoop metrics in Stackdriver
  • Fixed Hue service failed to start issue on 1.3-deb9 images.

August 31, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.93-deb8, 1.1.84-deb8, 1.2.47-deb8, 1.3.7-deb8, 1.0.93-deb9, 1.1.84-deb9, 1.2.47-deb9, 1.3.7-deb9.
  • Fixed issue in which workers would fail to join the cluster when using the connectors init action.
  • Fixed issue in which Hive jobs would fail if they were submitted during the first minute after cluster creation.
  • Fixed init actions flakiness due to E: Could not get lock /var/lib/dpkg/lock error.

August 30, 2018

August 24, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.92-deb8, 1.1.83-deb8, 1.2.46-deb8, 1.3.6-deb8, 1.0.92-deb9, 1.1.83-deb9, 1.2.46-deb9, 1.3.6-deb9.
  • Image 1.0-1.2 only: Cloud Storage and BigQuery connector upgrades (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to 1.6.8 version
    • BigQuery connector has been upgraded to 0.10.9 version
  • Image 1.3 only: Cloud Storage connector upgrade to 1.9.5 version (for more information, review the change notes in the GitHub repository)
  • Image 1.3 with Debian 9 only:
    • Upgrade Spark to 2.3.1.
    • Add HBase 1.3.2.
    • Add Flink 1.5.0.
  • Fixed issue in Dataproc Image version 1.2 where conflicting ASM JARs occasionally caused Zeppelin to crash.
  • Fix issue in Dataproc Image version 1.3 where Snappy compression in the ORC file format in Spark was broken. This was a regression introduced in Image Version 1.3.3 while resolving SPARK-24018. After this fix, Parquet and ORC can both use Snappy compression.

August 16, 2018

  • New Debian 9 based images are available for image versions 1.0-1.3. They can be accessed by appending '-deb9' to the existing version tracks (for example 1.2-deb9).
  • Until November 2, 2018, existing 1.X image versions will use debian 8 images (for example 1.3 will resolve to 1.3.Y-deb8). On November 2, 2018, existing 1.X image versions will switch to Debian 9 images. Debian 8 will not be used in new image releases on and after November 2, 2018.
  • New sub-minor versions of Cloud Dataproc images - 1.0.91-deb8, 1.0.91-deb9, 1.1.82-deb8, 1.1.82-deb9, 1.2.45-deb8, 1.2.45-deb9, 1.3.5-deb8, 1.3.5-deb9.
  • Security fix: Install Linux Kernel 4.9 in all image versions to get security fixes for CVE-2018-3590 and CVE-2018-3591 in all new Debian 8 images.

August 10, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.90, 1.1.81, 1.2.45, 1.3.5
  • Set maximum number of open files to 65535 for all Systemd services.

August 03, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.89, 1.1.80, 1.2.44, 1.3.4
  • In HA clusters, hadoop.security.token.service.use_ip is now set to false.
  • Upgraded Hadoop to 2.8.4. (Dataproc 1.2)
  • Fixed issue in which Hive jobs would fail on 1.3 HA clusters.
  • Fixed the default value of mapreduce.jobhistory.recovery.store.fs.uri by setting it back to ${hadoop.tmp.dir}/mapred/history/recoverystore. It was set to hdfs:///mapred/history/recoverystore in error as part of the July 6 release.
  • Backported ZOOKEEPER-1576 into ZooKeeper 3.4.6 in Dataproc 1.2 and 1.3. This bug caused Zookeper connections to fail if any one of the servers failed to resolve.

July 31, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.3.3
  • Changes to 1.3 image only:
    • Disabled node blacklisting in Tez jobs (set tez.am.node-blacklisting.enabled=false). This affects all Hive jobs, which run on Tez by default.
  • Fixed issue breaking native Snappy compression in spark-shell (SPARK-24018) and Zeppelin.
  • Fixed issue where gsutil and gcloud do not work on cluster VMs when the ANACONDA optional component is selected.

July 18, 2018

July 13, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.88, 1.1.79, 1.2.43, 1.3.2
  • Cloud Dataproc now adds resource location to generated cloud audit logs.

July 10, 2018

  • Cloud Dataproc is now available in the us-west2 region (Los Angeles).

July 06, 2018

  • Announcing the alpha release of Cloud Dataproc Optional Components. This feature allows users to specify additional components to install when creating new Dataproc clusters.
  • New sub-minor versions of Cloud Dataproc images - 1.0.87, 1.1.78, 1.2.42, 1.3.1
  • Changes to 1.3 image only:
    • The per-driver Spark web UI has been re-enabled.
    • The HCatalog library is installed by default.
  • MapReduce job history server recovery is now enabled by default.
  • A race condition in HA cluster creation with the resolveip utility has been resolved.

June 29, 2018

  • Cloud Dataproc 1.3 - A new image version for Cloud Dataproc is now generally available.
    • Image version 1.3 will become the default image version for new clusters starting 07/30/2018. See the Cloud Dataproc Version List for more information.Image version 1.3 includes the following changes:
    • Apache Spark has been updated to version 2.3.0.
    • Apache Hadoop has been updated to version 2.9.0.
    • Apache Hive has been updated to version 2.3.2.
    • Hive runs on Apache Tez by default.
    • The YARN Timeline Server is enabled by default.
  • Announcing the general availability (GA) release of Cloud Dataproc Custom Images (was Beta). This feature allows users to create and save custom images with packages pre-installed. These custom images can then be used to create Cloud Dataproc clusters.
  • New sub-minor versions of Cloud Dataproc images - 1.0.86, 1.1.77, 1.2.41, 1.3.0
  • Changes to 1.3 image only:
    • Cloud Storage connector was upgraded to version 1.9.0 (see the change notes in the GitHub repository).
    • The NFS Kernel Server is no longer installed.

June 27, 2018

June 22, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.85, 1.1.76, 1.2.40
  • Upgraded the Cloud Storage and BigQuery connectors in 1.0.85, 1.1.76, 1.2.40 (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to version 1.6.7
    • BigQuery connector has been upgraded to version 0.10.8

June 15, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.84, 1.1.75, 1.2.39
  • Initialization Action output is now available in Stackdriver under google.dataproc.startup log.
  • Cloud Dataproc will refuse to create new clusters based on most images created before 2018-02-14. Customers do not need to change minor versions, but if they specify a subminor version that falls into this group, they will need to use a newer subminor version (e.g. 1.1.39 can not be used for new clusters, but 1.1 and 1.1.73 are valid).

June 11, 2018

  • Cloud Dataproc is now available in the europe-north1 region (Finland).

June 08, 2018

  • Google Cloud SDK 203.0.0 (2018-05-29)
    • Changes include:
      • Added gcloud beta dataproc workflow-templates instantiate-from-file to enable instantiation of workflow templates directly from a YAML file.
      • Added gcloud beta dataproc clusters create-from-file to enable creation of clusters directly from a YAML file.
    • See the Cloud SDK reference documentation for more information.
  • New sub-minor versions of Cloud Dataproc images - 1.0.83, 1.1.74, 1.2.38
  • Change the jdbc connect string passed to beeline when submitting Hive jobs to high availability clusters through the Cloud Dataproc Jobs API. The new connect string takes advantage of high availability of HiveServer2.
  • WorkflowTemplates will now correctly report Job failures.

May 28, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.82, 1.1.73, 1.2.37
  • Hive Server 2 now runs all three masters in High Availablility mode.
  • Preview image changes (Dataproc 1.3):
    • Now requires a 15 GB minimum boot disk size.
    • The NameNode Service RPC port has changed from 8040 to 8051.
    • The SPARK_HOME environment variable is now globally set.
  • ALPN boot jar removed from 1.2. This regression was introduced in 1.2.35.

May 21, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.81, 1.1.72, 1.2.36
  • Upgraded the Cloud Storage and BigQuery connectors in 1.0.81, 1.1.72, 1.2.36 (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to version 1.6.6
    • BigQuery connector has been upgraded to version 0.10.7
  • New version of Cloud Dataproc 1.3 preview image:
    • Remove BigQuery connector from image. Users should instead include the BigQuery connector with jars for their jobs.
    • Cloud Dataproc 1.3 is not supported
    • See Cloud Dataproc version list for more information.
  • Hive Metastore is configured to run on all three masters in High Availability mode
  • Fixed an issue in which accelerator quota was being incorrectly validated, for example, cluster creation might fail with an "Insufficient 'NVIDIA_K80_GPUS' quota" error, even though quota was sufficient.

May 14, 2018

  • New Cloud Dataproc 1.3 image track available in preview.
    • Changes include:
      • Spark 2.3, Hadoop 2.9, Hive 2.3, Pig 0.17, Tez 0.9
      • Hive on Tez by default (no need for the Tez initialization action).
    • Cloud Dataproc 1.3 is not officially supported.
    • See Cloud Dataproc version list for more information.

May 04, 2018

  • Fixed issue in which preemptible workers were not getting cleaned up from node membership files once they had left the cluster.

April 27, 2018

April 20, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.77, 1.1.68, 1.2.32
  • Changed the Namenode HTTP port from 50070 to 9870 on HA clusters in preview image. WebHDFS, for example, is accessible at http://clustername-m-0:9870/webhdfs/v1/. This is consistent with standard and single node clusters in Dataproc 1.2+. Dataproc 1.0 and 1.1 clusters will continue to use port 50070 for all cluster modes.
  • Upgraded the Cloud Storage and BigQuery connectors (for more information, review the change notes in the GitHub repository):
    • Cloud Storage connector has been upgraded to version 1.6.5
    • BigQuery connector has been upgraded to version 0.10.6
  • Fixed issue where cluster can go into ERROR state due to error when resizing a managed instance group.
  • Backported PIG-4967 and MAPREDUCE-6762 into Cloud Datproc image version 1.2 to fix an occasional NullPointerException in Pig jobs.
  • Fixed an uncommon issue in which a Cloud Dataproc agent restart during a small window of a cluster downscale operation could cause problems decommissioning data nodes.

April 13, 2018

  • Fixed rare issue where Cloud Dataproc agent fails to initialize HDFS configuration and reports too few DataNodes reporting.
  • Fixed how Cloud Dataproc determines that HDFS decommission is complete.

April 06, 2018

March 30, 2018

March 23, 2018

March 22, 2018

March 16, 2018

March 09, 2018

  • Fixed an issue where ZooKeeper was not configured to periodically clean up its data directories.

March 05, 2018

  • Cloud Dataproc Custom Images - Beta. Users can now create and save custom images that have their packages pre-installed. The custom images can then be used to create Cloud Dataproc clusters.
  • New sub-minor versions of Cloud Dataproc images - 1.0.70, 1.1.61, 1.2.25.
  • An optional requestId field has been added to CreateCluster, UpdateCluster, DeleteCluster, and SubmitJob. The requestId field can be used to prevent the processing of duplicate requests (subsequent requests with a requestId that is the same as a previous requestId are ignored).
  • Increased the MapReduce and Spark History Server heap sizes when running on large master nodes.
  • Fixed an issue where initialization actions could fail to execute with the error "errno 26 Text file is busy".

February 23, 2018

February 16, 2018

  • New sub-minor versions of Cloud Dataproc images - 1.0.68, 1.1.59, 1.2.23.
  • Updating cluster labels now also updates labels on PDs attached to master and primary worker VMs.
  • Fixed an issue where cluster deletion could be slow if multiple delete cluster requests were in progress.
  • Fixed an issue where jobs became stuck if logging failed.
  • Fixed an issue where a cluster downsize operation failed when the dataproc agent incorrectly identified HDFS datanode decommission as stuck.
  • Fixed an issue where the dataproc agent incorrectly reported two YARN metrics.

February 09, 2018

  • New sub-minor versions of the Cloud Dataproc images - 1.0.67, 1.1.58, 1.2.22.

  • The High Availability Mode feature is now in public release (was Beta). Cloud Dataproc clusters can be created with high availability mode enabled. This is an optional feature when creating a cluster. In high availability mode, Cloud Dataproc clusters have three master nodes instead of one. This enables both HDFS High Availability and YARN High Availability to allow uninterrupted YARN and HDFS operations despite any single-node failures or reboots.

    This feature is available when creating clusters with the [gcloud](https://cloud.google.com/sdk/gcloud/reference/dataproc/) command-line tool, the Cloud Dataproc REST API, and Google Cloud Platform Console. See High Availability Mode for more information.

  • An Update Cluster operation now returns a DONE operation if the update request has no work to perform.

  • Fixed an issue where a workflow can get stuck due to a manually deleted cluster.

February 02, 2018

  • Added support for setting hadoop-env, mapred-env, spark-env, and yarn-env dataproc properties through new prefixes. NOTE: applies only to new subminor image versions.
  • Added a button to link to Stackdriver logs for a cluster on the Google Cloud Platform Console Cluster details page.
  • Fixed a Hadoop issue where an insufficient number of Datanodes were reporting.
  • Sped up commitJob on Cloud Storage for jobs with many last-stage (reduce) tasks.

January 10, 2018

  • It is now possible to instantiate Dataproc workflows directly without creating a WorkflowTemplate by using the new InstantiateInline method.
  • Announcing the Beta release of Cloud Dataproc Persistent Solid State Drive (PD-SSD) Boot Disks, which allows you to create clusters that use PD-SSDs for the master and worker node boot disks.
  • Cloud Dataproc is now available in the northamerica-northeast1 region (Montréal, Canada).
  • Cloud Dataproc is now available in the europe-west4 region (Netherlands).
  • New sub-minor versions of the Cloud Dataproc images - 1.0.63, 1.1.54, 1.2.18.
  • Automatic retry of commitJob (introduced in MAPREDUCE-5485) is now enabled by default; set mapreduce.fileoutputcommitter.failures.attempt to 1 to revert to the old behavior.
  • Applied patch for CVE-2017-5754 ("Meltdown") along with other security patches referenced in DSA-4082-1.
  • Local SSDs are now properly reformatted on boot after an ungraceful host migration; previously, ungraceful host migrations on nodes with local SSDs could cause workers to become defunct.
  • Improved reliability of High Availability cluster startup for cases where one or more masters' startup is delayed.

December 20, 2017

  • The Google Cloud Dataproc Graceful Decommissioning feature is now in public release (was Beta). Graceful Decomissioning enables the removal of nodes from the cluster without interrupting jobs in progress. A user-specified timeout specifies how long to wait for jobs in progress to finish before forcefully removing nodes. This feature is available when updating clusters using the gcloud command-line tool, the Cloud Dataproc REST API, and Google Cloud Platform Console. See Graceful Decommissioning for more information.

  • The Single Node Clusters feature is now in public release (was Beta). Single node clusters are Cloud Dataproc clusters with only one node that acts as the master and worker. Single node clusters are useful for a number of activities, including development, education, and lightweight data science.

    This feature is available when creating clusters with the gcloud command-line tool, the Cloud Dataproc REST API, and Google Cloud Platform Console. See Single node clustersfor more information.

December 08, 2017

  • The Restartable Jobs feature is now in public release (was Beta). Cloud Dataproc jobs have an optional setting to restart failed jobs. When you set a job to restart, you specify the maximum number of retries per hour (maximum is 10). Restartable jobs allow you to mitigate common types of job failure, and are especially useful for long-running and streaming jobs. This feature is available when submitting jobs using the gcloud command-line tool, the Cloud Dataproc REST API, and Google Cloud Platform Console. See Restartable jobs for more information.

November 17, 2017

  • New sub-minor versions of the Cloud Dataproc images - 1.0.58, 1.1.49, 1.2.13.
  • Added new optimization that increases the performance of list operations for operations and jobs when tags are used.

November 10, 2017

  • New sub-minor versions of the Cloud Dataproc images - 1.0.57, 1.1.48, 1.2.12.
  • Apache Hadoop has been upgraded to 2.8.2 in the Cloud Dataproc 1.2 image.

November 01, 2017

  • When using workflow cluster selectors, if more than one cluster matches the specified label(s), Cloud Dataproc will select the cluster with the most free YARN memory. This change replaces the old behavior of choosing a random cluster with the matching label.
  • New sub-minor versions of the Cloud Dataproc images - 1.0.56, 1.1.47, 1.2.11.
  • HTTP 404 and 409 errors will now show the full resource name in order to provide more useful error messages.
  • Fixed a bug that prevented workflow templates from handling /locations/ in resource names.

October 31, 2017

Cloud Dataproc is now available in the asia-south1 region (Mumbai, India).

October 24, 2017

October 17, 2017

  • Fixed a bug where HTTP keep-alive was causing java.lang.NullPointerException: ssl == null errors when accessing Cloud Storage.
  • The Apache Oozie initialization action has been fixed to work with Cloud Dataproc 1.2.

October 11, 2017

  • The fluentd on Cloud Dataproc clusters has been reconfigured to concatenate multi-line error messages. This should make error messages easier to locate.
  • Clusters created with Cloud Dataproc Workflows can now use auto-zone placement.
  • Starting with this release, sub-minor releases to the Cloud Dataproc images will be mentioned in the release notes.
  • New sub-minor versions of the Cloud Dataproc images - 1.0.53, 1.1.44, 1.2.8.
  • Fixed a bug reading ORC files in Hive 2.1 on Cloud Dataproc 1.1. To fix this issue, HIVE-17448 has been patched into to Hive 2.1.
  • Fixed an issue where Spark memoryOverhead was improperly set for clusters with high-memory master machines and low-memory workers. The memoryOverhead will now be appropriately set for these types of clusters.
  • The Cloud Dataproc agent has improved logic to start jobs in the order in which they were submitted.
  • The HUE initialization action has been fixed to work with Cloud Dataproc 1.2.
  • Fixed a bug where initialization action failures were not properly reported.

October 04, 2017

  • Cloud Dataproc Workflow Templates (Beta) – This new Cloud Dataproc resource allows jobs to be composed into a graph to execute on an ephemeral or an existing cluster. The template can create a cluster, run jobs, then delete the cluster when the workflow is finished. Graph progress can be monitored by polling a single operation. See Workflow templates—Overview for more information.

September 27, 2017

  • Cloud Dataproc Granular IAM (Beta) – Now you can set IAM roles and their corresponding permissions on a per-cluster basis. This provides a mechanism to have different IAM settings for Cloud Dataproc clusters. See the Cloud Dataproc IAM documentation for more information.
  • Fixed a bug which prevented Apache Pig and Apache Tez from working together in Cloud Dataproc 1.2. This fix was applied to Cloud Dataproc 1.1 in a previous release.
  • Fixed a bug involving Hive schema validation. This fix specifically addresses HIVE-17448 and HIVE-12274.

September 19, 2017

  • New Subminor Image Versions – The latest subminor image versions for 1.0, 1.1, and 1.2 now map to 1.0.51, 1.1.42, 1.2.6, respectively.

September 06, 2017

  • Cluster Scheduled Deletion (Beta) – Cloud Dataproc clusters can now be created with an scheduled deletion policy. Clusters can be scheduled for deletion either after a specified duration or at a specified time, or after a specified period of inactivity. See Cluster Scheduled Deletion for more information.

September 05, 2017

Cloud Dataproc is now available in the southamerica-east1 region (São Paulo, Brazil).

August 18, 2017

  • New Subminor Image Versions – The latest subminor image versions for 1.0, 1.1, and 1.2 now map to 1.0.49, 1.1.40, 1.2.4, respectively.
  • All Cloud Dataproc clusters now have a goog-dataproc-cluster-name label that is propagated to underlying Google Compute Engine resources and can be used to determine combined Cloud Dataproc related costs in exported billing data.
  • PySpark drivers are now launched under a changed process group ID to allow the Cloud Dataproc agent to correctly clean up misbehaving or cancelled jobs.
  • Fixed a bug where updating clusters labels and the number of secondary workers in a single update resulted in a stuck update operation and an undeletable cluster.

August 08, 2017

Beginning today, Cloud Dataproc 1.2 will be the default version for new clusters. To use older versions of Cloud Dataproc, you will need to manually select the version on cluster creation.

August 04, 2017

Graceful decomissioning – Cloud Dataproc clusters running Cloud Dataproc 1.2 or later now support graceful YARN decommissioning. Graceful decomissioning enables the removal of nodes from the cluster without interrupting jobs in progress. A user-specified timeout specifies how long to wait for jobs in progress to finish before forcefully removing nodes. The Cloud Dataproc scaling documentation contains details how enable graceful decomissioning.

Apache Hadoop on Cloud Dataproc 1.2 has been updated to version 2.8.1

August 01, 2017

Cloud Dataproc is now available in the europe-west3 region (Frankfurt, Germany).

July 21, 2017

  • Cloud Dataproc 1.2 – A new image version for Cloud Dataproc is now generally available: 1.2. It will become the default image version for new clusters starting in 2 weeks. See the Cloud Dataproc version list for more information. Some important changes included in this new image version:
    • Apache Spark has been updated to version 2.2.0.
    • Apache Hadoop has been updated to version 2.8.0.
    • The default security (SSL) provider used by the Cloud Storage connector has been changed to one based on Conscrypt. This change should more efficiently utilize the CPU for SSL operations. In many cases, this change should result in better read and write performance between Cloud Dataproc and Cloud Storage.
    • The reported block size for Cloud Storage is now 128MB.
    • Memory configuration for Hadoop and Spark have both been adjusted to improve performance and stability.
    • HDFS daemons no longer use ephemeral ports in accordance with new port assignments outlined in HDFS-9427. This eliminates certain rare race conditions that could cause occasional daemon startup failures.
    • YARN Capacity Scheduler fair ordering from YARN-3319 is now enabled by default.

Starting with the Cloud Dataproc 1.2 release, the ALPN boot jars are no longer provided on the Cloud Dataproc image. To avoid Spark job breakage, upgrade Cloud Bigtable client versions, and bundle boringssl-static with Cloud Dataproc jobs. Our initialization action repository contains initialization actions to revert to the previous (deprecated) behavior of including the jetty-alpn boot jar. This change should only impact you if you use Cloud Bigtable or other Java gRPC clients from Cloud Dataproc.

July 11, 2017

  • Spark 2.2.0 in Preview – The Cloud Dataproc preview image has been updated to Spark 2.2.0.
  • Spark 2.2.0 in Preview – The Cloud Dataproc preview image has been updated to Spark 2.2.0.

June 28, 2017

  • Regional endpoints generally available – Regional endpoints for Cloud Dataproc are now generally available.
  • Autozone (Beta) – When you create a new cluster as an alternative to choosing a zone, you can use the Cloud Dataproc Auto Zone feature to let Cloud Dataproc select a zone within your selected region for the placement of the cluster.
  • Conscrypt for Cloud Storage connector – The default security (SSL) provider used by the Cloud Storage connector on the Cloud Dataproc preview image has been changed to one based on Conscrypt. This change should more efficiently utilize the CPU for SSL operations. In many cases, this change should result in better read and write performance between Cloud Dataproc and Cloud Storage.

June 26, 2017

The v1alpha1 and v1beta1 Cloud Dataproc APIs are now deprecated and cannot be used. Instead, you should use the current v1 API.

June 20, 2017

Cloud Dataproc is now available in the australia-southeast1 region (Sydney).

June 06, 2017

Cloud Dataproc is now available in the europe-west2 region (London).

April 28, 2017

Cloud Storage and BigQuery connector upgrades – The Cloud Storage connector has been upgraded to gcs-connector-1.6.1 and the BigQuery connector has been upgraded to bigquery-connector-0.10.2. For more information, review the Cloud Storage or BigQuery change notes in the GitHub repository.

The v1alpha1 and v1beta1 Cloud Dataproc APIs are now deprecated and cannot be used. Instead, you should use the current v1 API.

April 21, 2017

April 12, 2017

Apache Hive on Cloud Dataproc 1.1 has been updated to version 2.1.1.

April 07, 2017

Cloud Dataproc worker IAM role – A new Cloud Dataproc IAM role called Dataproc/Dataproc Worker has been added. This role is intended specifically for use with service accounts.

The Conscrypt security provider has been temporarily changed from the default to an optional security provider. This change was made due to incompatibilities with some workloads. The Conscrypt provider will be re-enabled as the default with the release of Cloud Dataproc 1.2 in the future. In the meantime, you can re-enable the Conscrypt provider when creating a cluster by specifying this Cloud Dataproc property:

--properties dataproc:dataproc.conscrypt.provider.enable=true

March 30, 2017

Conscrypt for Cloud Storage connector – The default security (SSL) provider used by the Cloud Storage connector has been changed to one based on Conscrypt. This change should more efficiently utilize the CPU for SSL operations. In many cases, this change should result in better read and write performance between Cloud Dataproc and Cloud Storage.

Updates to user labels applied to Cloud Dataproc clusters will now be applied to managed instance group templates. Since preemptible virtual machines are included in a managed instance group, label updates are now applied to preemptible VMs.

March 17, 2017

The gcloud command now requires a double dash (--) between gcloud-specific arguments and arguments to those commands. For example, if you used this command in the past:

gcloud dataproc jobs submit spark --cluster example-cluster \
    --class sample_class --jars jar_file 1000

The new format for the command requires a double-dash with a space before and after the double dash:

gcloud dataproc jobs submit spark --cluster example-cluster \
    --class sample_class --jars jar_file -- 1000

.

As mentioned in the February 9th release notes, Cloud Audit Logs for Cloud Dataproc are no longer emitted to the dataproc_cluster resource type. Starting with this release, Cloud Audit Logs are emitted to the new cloud_dataproc_cluster resource type.

March 07, 2017

  • User labels – User labels with Cloud Dataproc resources are now generally available. You can add and update labels on Cloud Dataproc clusters and jobs. Labels are useful in situations such as cost accounting, work distribution, and testing.
  • Attaching GPUs to clusters (Beta) – Cloud Dataproc clusters now support Compute Engine GPUs. Clusters can have 1-8 GPUs attached to master and worker nodes. These GPUs can be used with applications on the cluster, such as Apache Spark. Attaching GPUs may benefit some types of data processing jobs.

March 01, 2017

  • Restartable jobs (Beta) – Cloud Dataproc jobs now have an optional setting to restart jobs that have failed. When you set a job to restart, you specify the maximum number of retries per hour. Restartable jobs allow you to mitigate common types of job failure and are especially useful for long-running and streaming jobs.
  • Single node clusters (Beta) – Single node clusters are Cloud Dataproc clusters with only one node that acts as the master and worker. Single node clusters are useful for a number of activities, including development, education, and lightweight data science.

February 09, 2017

  • Cloud Dataproc Stackdriver Logging Changes
    • With new images, cluster logs are now exported to Stackdriver as resource type cloud_dataproc_cluster (was previously dataproc_cluster).
    • Cloud Audit logs will be emitted to both cloud_dataproc_cluster and dataproc_cluster (deprecated) until the March 9th release.
    • Stackdriver logs for new images are indexed first by cluster name and then cluster UUID to assist in filtering logs by cluster name or cluster instance.
  • Cloud Dataproc Stackdriver Monitoring Changes
  • Cloud Dataproc User Labels Changes

January 19, 2017

  • Cloud Dataproc 1.2 preview – The preview image has been updated to reflect the planned Cloud Dataproc 1.2 release. This image includes Apache Spark 2.1 and Apache Hadoop 2.8-SNAPSHOT. This preview image is provided so we can provide access to Hadoop 2.8 in Dataproc 1.2 once Hadoop 2.8 is formally released and access to release candidates.

January 05, 2017

  • Cloud Storage and BigQuery connector upgrades – The Cloud Storage connector has been upgraded to gcs-connector-1.6.0 and the BigQuery connector has been upgraded to bigquery-connector-0.10.1. For more information, review the Cloud Storage or BigQuery change notes in the GitHub repository.
  • The diagnose command has been updated to include the jstack output of the agent and spawned drivers.

December 16, 2016

  • Google Stackdriver Agent Installed – The Stackdriver monitoring agent is now installed by default on Cloud Dataproc clusters. The Cloud Dataproc Stackdriver monitoring documentation has information on how to use Stackdriver monitoring with Cloud Dataproc. The agent for monitoring and logging can be enabled and disabled by adjusting the cluster properties when you create a cluster.
  • Cloud Dataproc 1.1.15 and 1.0.24 – The 1.1 and 1.0 images have been updated with non-impacting updates, bug fixes, and enhancements.

December 07, 2016

  • Cloud Dataproc 1.1.14 and 1.0.23 – The 1.1 and 1.0 images have been updated with non-impacting updates, bug fixes, and enhancements.
  • Increased number of situations where Cloud-Dataproc services are automatically restarted by systemd on clusters in the event of unexpected or unhealthy behavior.
  • Starting with this release, the Google Cloud Dataproc API must be enabled for your project for Cloud Dataproc to function properly. You can use the GCP Console to enable the Cloud Dataproc API. Existing projects with the Cloud Dataproc API enabled will not be impacted.

November 29, 2016

  • Custom service account support – When creating a Cloud Dataproc cluster, you can now specify a user-managed (non-default) service account. This service account will be used to run the Compute Engine virtual machines in your cluster. This enables much more fine-grained permissions across services for each individual cluster. See the service account documentation for more information.
  • Cloud Dataproc 1.1.13 and 1.0.22 – The 1.1 image for Cloud Dataproc has been updated to include support for Apache Spark 2.0.2, Apache Zeppelin 0.6.2, and Apache Flink 1.1.3. The 1.1 and 1.0 images have also been updated with non-impacting bug fixes and enhancements. See the Cloud Dataproc version list for more information about Cloud Dataproc image versions.

November 14, 2016

  • Fixed an issue where the --jars argument was missing from gcloud dataproc jobs submit pyspark command.

November 08, 2016

  • Google BigQuery connector upgrade – The BigQuery connector has been upgraded to bigquery-connector-0.10.1-SNAPSHOT. This version introduces the new IndirectBigQueryOutputFormat that uses Hadoop output formats that write directly to a temporary Cloud Storage bucket, and issues a single BigQuery load job per Hadoop/Spark job at job-commit time. For more information, review the BigQuerychange notes in the GitHub repository.

November 07, 2016

November 02, 2016

  • User Labels [BETA] – You can now apply user-specified key=value labels to Cloud Dataproc clusters and jobs. This allows you to group resources and related operations for later filtering and listing. As an example, you can use labels with clusters to break out Cloud Dataproc usage by groups or individuals. For more information see the user labels documentation.
  • Fixed an issue where failures during a cluster update caused the cluster to fail. Now, update failures return the cluster to Running state.
  • Fixed an issue where submitting a large number of jobs rapidly or over a long period of time caused a cluster to fail.
  • Increased the maximum number of concurrent jobs per cluster.

October 18, 2016

  • Fixed an issue where HiveServer2 was not healthy for up to 60 seconds after the cluster was deployed. Hive jobs should now successfully connect to the required HiveServer2 immediately after a cluster is deployed.

October 11, 2016

  • Cloud Storage and BigQuery connector upgrades – The Cloud Storage connector has been upgraded to gcs-connector-1.5.4 and the BigQuery connector has been upgraded to bigquery-connector-0.8.0. For more information, review the Cloud Storage or BigQuerychange notes in the GitHub repository.
  • dataproc.localssd.mount.enable – Added the new property dataproc.localssd.mount.enable that can be set at cluster deployment time to make Cloud Dataproc ignore local SSDs. If set, Cloud Dataproc will use the main persistent disks for HDFS and temporary Hadoop directories so the local SSDs can be used separately for user-defined purposes. This property can be set by using the argument --properties dataproc:dataproc.localssd.mount.enable=false when creating a Cloud Dataproc cluster.
  • Fixed an issue where CPU quota validation for preemptible virtual machines was being performed against the non-preemptible CPU quota even when preemptible CPU quota was set.

October 07, 2016

  • GCP Console
    • Now, up to 8 local SSDs can be added to worker nodes. The previous limit was 4.
    • When looking at a cluster's details, the "Jobs" page now shows Stop and Delete buttons for every job in the list. Previously, the buttons were only visible on the row where the mouse hovered.
  • Optimized the listing of resources by state and cluster UUID. This should reduce several list operations from seconds to milliseconds.

September 29, 2016

  • Hadoop High Availability Mode [BETA] – Cloud Dataproc clusters can be created with high availability mode enabled. This is an optional feature when creating a cluster. In high availability mode, Cloud Dataproc clusters have three master nodes instead of one. This enables both HDFS High Availability and YARN High Availability to allow uninterrupted YARN and HDFS operations despite any single-node failures or reboots.

    Presently, this feature is available when creating clusters with the [gcloud](https://cloud.google.com/dataproc/docs/gcloud-installation) command-line tool or the Cloud Dataproc REST API. A future release will enable support for creating clusters with high availability in the Google Cloud Platform Console.

    See the high availability mode documentation for more information.

  • Optimized how jobs are listed based on state or cluster uuid. This should significantly decrease the time required to list jobs.

September 22, 2016

  • Cloud Storage and BigQuery connector upgrades – The Cloud Storage connector has been upgraded to gcs-connector-1.5.3 and the BigQuery connector has been upgraded to bigquery-connector-0.7.9. For more information, review the change notes in the GitHub repository.
  • While Cloud Dataproc has been using Java 8 since its Beta launch in September 2015, there is now a hard dependency on Java 8 or higher.
  • The --preemptible-worker-boot-disk-size command no longer requires that you specify 0 preemptible workers if you do not want to add preemptible machines when you create a cluster.

September 16, 2016

  • Preemptible boot disk sizes - The disk size for preemptible workers can now be set via the gcloud command-line tool at cluster creation, even when preemptibles are not added to a cluster using the commend --preemptible-worker-boot-disk-size.

September 01, 2016

  • Identity & Access Management support [BETA] - Cloud Dataproc now has beta support for Identity and Access Management (IAM). Cloud Dataproc IAM permissions allow users to perform specific actions on Cloud Dataproc clusters, jobs, and operations. See Cloud Dataproc Permissions and IAM Roles for more information.
  • LZO support - Cloud Dataproc clusters now natively support the LZO data compression format.
  • Google Stackdriver logging toggle - It is now possible to disable Google Stackdriver logging on Cloud Dataproc clusters. To disable Stackdriver logging, use the command --properties dataproc:dataproc.logging.stackdriver.enable=false when creating a cluster with the gcloud command-line tool.
  • Cluster resource definitions for newly deployed clusters now display a fully resolved sub-minor image-version (e.g. 1.0.11 instead of 1.0). This makes it easier to temporarily revert to an older sub-minor version. See the Cloud Dataproc versioning for more information.
  • The message displayed after submitting a long-running operation in the GCP Console, such as creating or deleting a cluster, will now indicate the operation has been "submitted" rather than "has succeeded."

August 25, 2016

  • Cloud Storage and BigQuery connector upgrades – The Cloud Storage connector has been upgraded to gcs-connector-1.5.2 and the BigQuery connector has been upgraded to bigquery-connector-0.7.8, which bring performance improvements. See the release notes for the gcs-connector and bigquery-connector for more information.
  • Apache Zeppelin 0.6.1 – The Apache Zeppelin package built for Cloud Dataproc and installable with this initialization action has been upgraded to version 0.6.1. This new version of Zeppelin brings support for Google BigQuery.

Cloud Dataproc 1.1 default – Cloud Dataproc 1.1 is now the default image version for new clusters.

  • Fixed an issue where adding many (~200+) nodes to a cluster would cause some nodes to fail.
  • Fix an issue where output from initialization actions that timed out was not copied to Cloud Storage.

August 16, 2016

Image versions released after Cloud Dataproc became generally available, starting with 1.0, will be subject to the Cloud Dataproc versioning policy.

The two Cloud Dataproc image versions released during the Cloud Dataproc beta, 0.1 and 0.2, will no longer receive updates. You can continue to use the beta images; however, no new updates, such as bug fixes and connector updates, will be applied to these two deprecated image versions.

August 08, 2016

Cloud Dataproc 1.1 – A new image version, Cloud Dataproc 1.1, has been released. Several components have been updated for this image version including:

To create a cluster with the 1.1 image, you can use the gcloud command-line tool with the --image-version argument, such as gcloud dataproc clusters create --image-version 1.1.

Cloud SDK release 121.0.0 – Updated several gcloud dataproc arguments.

  • The --preemptible-worker-boot-disk-size argument has been promoted to general availability and can be used to adjust the persistent disk size (in GB) of preemptible workers.
  • The --master-boot-disk-size-gb and --worker-boot-disk-size-gb arguments have been removed. Use --master-boot-disk-size and --worker-boot-disk-size instead.

August 02, 2016

Cloud Storage and BigQuery connector upgrades – The Cloud Storage connector has been upgraded to gcs-connector-1.5.1 and the BigQuery connector has been upgraded to bigquery-connector-0.7.7. See the release notes for the gcs-connector and bigquery-connector for more information.

Updated preview image – Several preview image components have been updated, including:

Fixed an issue in which the NFS-based Cloud Storage consistency cache would not get cleaned on long-running clusters with sustained high file creation rates (> ~1,000,000 files per hour for a sustained period of time).

July 19, 2016

  • Support for new us-west1 region - Cloud Dataproc is available from day one in the newly announced west-1 region. As mentioned in the announcement, some West Coast users may see reductions in latency.
  • Apache Spark upgrade to 1.6.2 - Apache Spark on the 1.0 Cloud Dataproc image version has been upgraded from 1.6.1 to 1.6.2.
  • Cloud Storage and BigQuery connector upgrades - The Cloud Storage connector has been upgraded to gcs-connector-1.5.0 and the BigQuery connector has been upgraded to bigquery-connector-0.7.6. These new versions bring a number of new features and fixes.
    • Appendable output streams - GHFS (Google Hadoop File System) now contains an option to enable support for appendable output streams. You can enable this option by setting the fs.gs.outputstream.type property to SYNCABLE_COMPOSITE.
    • Auto retries on 429 errors - HTTP 429 (rate limit) errors from Google APIs will now be automatically retried with a backoff.
    • Cloud Storage performance - Improved the Cloud Storage connector read performance, especially for lots of small reads or lots of seeks. See the detailed change log for more information.
  • GCP Console
    • The GCP Console now uses the Cloud Dataproc v1 instead of the v1beta1 API. Clicking on the equivalent REST link will show the appropriate v1 API paths and resource names.
  • Fixed an issue where some HDFS nodes did not join a cluster because their domain name could not be resolved on first boot.

July 01, 2016

  • gcloud command-line tool
    • Added the flag --preemptible-worker-boot-disk-size which can be used to adjust the boot disk size of preemptible workers. This was added in the gcloud beta track.
    • The --*-boot-disk-size-gb flag is now deprecated in all tracks and has been replaced by the --*-boot-disk-size commands.
  • Fixed a bug introduced in a June release that caused clusters to fail only after waiting for ~30 minutes. This occurred most frequently when initialization actions failed during cluster creation. Now clusters should fail within 1 minute of an initialization action failure.
  • Decreased job startup time for SparkSQL jobs with partitioned/nested directories by applying a patch for Spark (SPARK-9926)
  • Further optimized job startup time for any job with a lot of file inputs by applying a patch for Hadoop (HADOOP-12810)

June 10, 2016

May 04, 2016

  • Cloud SQL Initialization Action - Cloud Dataproc now has a Cloud SQL I/O and Hive Metastore initialization action. This initialization action installs a Google Cloud SQL proxy on every node in a Cloud Dataproc cluster. It also configures the cluster to store Apache Hive metadata on a given Cloud SQL instance.

April 29, 2016

  • The staging directory for a Cloud Dataproc job is now automatically cleared when a job completes.
  • If a cluster fails to delete properly, it will now be transitioned to a FAILED state instead of remaining in a DELETING state.
  • Fixed an issue which prevented the Cloud Dataproc --properties command from changing MapReduce properties.
  • Fixed a bug where an exception would be thrown when trying to set YARN log-aggregation to output to Cloud Storage (related to YARN-3269).

March 30, 2016

  • Spark 1.6.1 - The Cloud Dataproc image version 1.0 has been updated to include the Spark 1.6.1 maintenance release instead of Spark 1.6.0.
  • OSS upgrades - This release upgrades the Cloud Storage and Google BigQuery connectors to gcs-connector-1.4.5 and bigquery-connector-0.7.5, respectively.
  • It is now possible to specify --num-preemptible-workers 0 through the gcloud command-line tool. Previously this would fail.
  • Fixed a validation issue which produced 500 HTTP errors when the response should have been 400 bad input or 200 OK.
  • Resolved a cache validation issue and re-enabled re-enable directory inference for the Cloud Storage connector (fs.gs.implicit.dir.infer.enable).
  • Adjusted Compute Engine migration settings due to unexpected host failures - normal VMs will automatically restart after migration and preemptible machines will not. Previously all VMs were set to not automatically restart after a migration.
  • Addressed an issue where rapid job submission would result in a Too many pending operations on a resource error.

March 08, 2016

  • Subnetwork support - Cloud Dataproc now supports subnetworks through the gcloud command-line tool. You can now use the --subnet SUBNET command to specify a subnetwork when you create a Cloud Dataproc cluster.
  • Added strict validation of full compute resource URIs. The following patterns are supported:
    • https://<authority>/compute/<version>/projects/...
    • compute/<version>/projects/...
    • projects/...
  • Fixed an issue wher

February 22, 2016

  • Cloud Dataproc is now generally available! For more information, see our announcement blog post.

  • Custom compute engine machine types - Cloud Dataproc clusters now support custom Compute Engine machine types for both master and worker nodes. This means you can create clusters with customized amounts of virtual CPUs and memory. For more information, please read the Dataproc documentation for custom machine types.

  • OSS upgrades - We have released Cloud Dataproc version 1.0. This release includes an upgrade to Apache Spark 1.6.0 and Apache Hadoop 2.7.2. This release also includes new versions of the Cloud Storage and Google BigQuery connectors.

  • v1 API - The v1 API for Cloud Dataproc is now live. This API includes support for regionality along with minor fixes and adjustments. The API is available in the APIs Explorer and also has a Maven artifact in Maven Central. For more information, review the REST API documentation.

  • Support for --jars for PySpark - Added support for using the --jars option for PySpark jobs.

  • API auto-enable - Enabling the Cloud Dataproc API now automatically enables required dependent APIs, such as Cloud Storage and Google Compute Engine

  • Resolved several issues that occasionally caused some clusters to hang being scaled down.
  • Improved validation of certain types of malformed URLs, which previously failed during cluster deployment.

February 03, 2016

  • A new --image-version option has been added: preview
    • Unlike other numerical versions like 0.1 and 0.2, the preview version will contain newer Hadoop/Spark/Pig/Hive components targeted for potential release in the next stable Cloud Dataproc distribution version, and will change over time.
    • As of February 3, 2016, the preview version contains Spark 1.6.0, with the same Hadoop/Pig/Hive versions as Cloud Dataproc 0.2.
    • The preview option is being rolled out to the GCP Console gradually, so may not be visible in your account for another week or so. For all users, the preview option is accessible by deploying clusters with the gcloud command-line tool.
  • Improved reliability of the DeleteJob command.
  • Fixed a bug that caused jobs to remain in a RUNNING state after the job completed successfully.

January 27, 2016

  • Two new options have been added to the Cloud Dataproc gcloud command-line tool for adding tags and metadata to virtual machines used in Cloud Dataproc clusters. These tags and metadata will apply to both regular and preemptible instances.
    • The --tags option will add tags to the Google Compute Engine instances in a cluster. For example, using the argument --tags foo,bar,baz will add three tags to the virtual machine instances in the cluster.
    • The --metadata option will add metadata to the compute engine instances. For example, using --metadata 'meta1=value1,key1=value2' will add two key-value pairs of metadata.
  • Support for heterogeneous clusters where the master node and worker nodes have different amounts of memory. Some memory settings were previously based on the master node which caused some problems as described in this Stack Overflow question. Cloud Dataproc now better supports clusters with master and worker nodes which use different machine types.
  • GCP Console
    • The Output tab for a job now includes a Line wrapping option to make it easier to view job output containing very long lines
  • Fixed two issues which would sometimes cause virtual machines to remain active after a cluster deletion request was submitted
  • The Spark maxExecutors setting is now set to 10000 to avoid the AppMaster failing on jobs with many tasks
  • Improved handling for aggressive job submission by making several changes to the Cloud Dataproc agent, including:
    • Limiting the number of concurrent jobs so they are proportional to the memory of the master node
    • Checking free memory before scheduling new jobs
    • Rate limiting how many jobs can be scheduled per cycle
  • Improved how HDFS capacity is calculated before commissioning or decommissioning nodes to prevent excessively long updates

January 21, 2016

  • The dataproc command in the Google Cloud SDK now includes a --properties option for adding or updating properties in some cluster configuration files, such as core-site.xml. Properties are mapped to configuration files by specifying a prefix, such as core:io.serializations. This command makes it possible to modify multiple properties and files when creating a cluster. For more information, see the Cloud Dataproc documentation for the --properties command.
  • GCP Console
    • An option has been added to the "Create Clusters" form to enable the cloud-platform scope for a cluster. This lets you view and manage data across all Google Cloud Platform services from Cloud Dataproc clusters. You can find this option by expanding the Preemptible workers, bucket, network, version, initialization, & access options section at the bottom of the form.
  • SparkR jobs no longer immediately fail with a "permission denied" error (Spark JIRA issue)
  • Configuring logging for Spark jobs with the --driver-logging-levels option no longer interferes with Java driver options
  • GCP Console
    • The error shown for improperly-formatted initialization actions now properly appears with information about the problem
    • Very long error messages now include a scrollbar so the Close button remains on-screen re ## January 7, 2016 #### Bugfixes
  • Fixed issue in Dataproc version 0.1 that caused zero-byte _SUCCESS and _FAILURE files for each job to be continually re-written to Cloud Storage.

December 16, 2015

  • Cloud Dataproc clusters now have vim, git, and bash-completion installed by default
  • The Cloud Dataproc API now has an official Maven artifact, Javadocs, and a downloadable .zip file
  • GCP Console
    • Properties can now be specified when submitting a job, and can be seen in the Configuration tab of a job
    • A Clone button has been added that allows you to easily copy all information about a job to a new job submission form
    • The left-side icons for Clusters and Jobs are now custom icons rather than generic ones
    • An Image version field has been added to the bottom of the create cluster form that allows you to select a specific Cloud Dataproc image version when creating a cluster
    • A VM Instances tab has been added on the cluster detail page, which you can use to display a list of all VMs in a cluster and easily SSH into the master node
    • An Initialization Actions field has been added to the bottom of the create cluster form, which allows you to specify initialization actions when creating a cluster
    • Paths to Cloud Storage buckets that are displayed in error messages are now clickable links.
  • Forced distcp settings to match mapred-site.xml settings to provide additional fixes for the distcp command (see this related JIRA)
  • Ensured that workers created during an update do not join the cluster until after custom initialization actions are complete
  • Ensured that workers always disconnect from a cluster when the Cloud Dataproc agent is shutdown
  • Fixed a race condition in the API frontend that occurred when validating a request and marking cluster as updating
  • Enhanced validation checks for quota, Cloud Dataproc image, and initialization actions when updating clusters
  • Improved handling of jobs when the Cloud Dataproc agent is restarted
  • GCP Console
    • Allowed duplicate arguments when submitting a job
    • Replaced generic Failed to load message with details about the cause of an error when an error occurs that is not related to Cloud Dataproc
    • When a single jar file for a job is submitted, allowed it to be listed only in the Main class or jar field on the Submit a Job form, and no longer required it to also be listed in the Jar files field

November 18, 2015

  • Version selection - With the release of Cloud Dataproc version 0.2, you can now select among different versions of Cloud Dataproc (see Cloud Dataproc Versioning for information on support for previous versions and Cloud Dataproc Version List a list of the software components supported in each version). You can select a Cloud Dataproc version when creating a cluster through the Cloud Dataproc API, Cloud SDK (using the gcloud beta dataproc clusters create --image-version command) or through the https://console.cloud.google.com/. Note that within four days of the release of a new version in a region, the new version will become the default version used to create new clusters in the region.

  • OSS upgrades - We have released Cloud Dataproc version 0.2. The new Spark component includes a number of bug fixes. The new Hive component enables use of the hive command, contains performance improvements, and has a new metastore.

  • Connector updates - We released updates to our BigQuery and Google Cloud Storage connectors (0.7.3 and 1.4.3, respectively.) These connectors fix a number of bugs and the new versions are now included in Cloud Dataproc version 0.2.

  • Hive Metastore - We introduced a MySQL-based per-cluster persistent metastore, which is shared between Hive and SparkSQL. This also fixes the hive command.

  • More Native Libraries - Cloud Dataproc now includes native Snappy libraries. It also includes native BLAS, LAPACK and ARPACK libraries for Spark's MLlib.

  • Clusters --diagnose command - The Cloud SDK now includes a --diagnose command for gathering logging and diagnostic information about your cluster. More details about this command are available in the Cloud Dataproc support documentation.

  • Fixed the ability to delete jobs that fast-failed before some cluster and staging directories were created
  • Fixed some remaining errors with vmem settings when using the distcp command
  • Fixed a rare bug in which underlying Compute Engine issues could lead to VM instances failing to be deleted after the Cloud Dataproc cluster had been successfully deleted
  • Hive command has been fixed
  • Fixed error reporting when updating the number of workers (standard and preemptible) in a cluster
  • Fixed some cases when Rate Limit Exceeded errors occurred
  • The maximum cluster name length is now correctly 55 instead of 56 characters
  • GCP Console
    • Cluster list now includes a Created column, and the cluster configuration tab now includes a Created field, telling the creation time of the cluster
    • In the cluster-create screen, cluster memory sizes greater than 999 GB are now displayed in TB
    • Fields that were missing from the PySpark and Hive job configuration tab (Additional Python Files and Jar Files) have been added
    • The option to add preemptible nodes when creating a cluster is now in the "expander" at the bottom of the form
    • Machine types with insufficient memory (less than 3.5 GB) are no longer displayed in the list of machine types (previously, selecting one of these small machine types would lead to an error from the backend
    • The placeholder text in the Arguments field of the submit-job form has been corrected

Core service improvements

  • If set, a project's default zone setting is now used as the default value for the zone in the create-cluster form in the GCP Console.

Optimizations

  • Hive performance has been greatly increased, especially for partitioned tables with a large number of partitions
  • Multithreaded listStatus has now been enabled, which should speed up job startup time for FileInputFormats reading large numbers of files and directories in Cloud Storage

October 23, 2015

GCP Console: Added support for adding, editing, and removing preemptible instances in clusters.

October 15, 2015

  • Fixed a bug in which DataNodes failed to register with the NameNode on startup, resulting in less-than-expected HDFS capacity.
  • Prevented the submission of jobs in an Error state.
  • Fixed bug that prevented clusters from deleting cleanly in some situations.
  • Reduced HTTP 500 errors when deploying Cloud Dataproc clusters.
  • Corrected distcp out-of-memory errors with better cluster configuration.
  • Fixed a situation in which jobs failed to delete properly and were stuck in a Deleting state.

Core service improvements

  • Provided more detail about HTTP 500 errors instead of showing 4xx errors.
  • Added information on existing resources for Resource already exists errors.
  • Specific information now provided instead of generic error message for errors related to Cloud Storage.
  • Listing operations now support pagination.

Optimizations

  • Significantly improved YARN utilization for MapReduce jobs running directly against Cloud Storage.
  • Made adjustments to yarn.scheduler.capacity.maximum-am-resource-percent to enable better utilization and concurrent job support.